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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.

Empowering leadership has a wide range of positive individual employee-related outcomes. However, a limited number of research studies are available emphasizing the overall organization-related outcomes. The major aim of this study is to delve into the function of organizational identification and intellectual capital (structural, relational and human) in mediating the relationship between empowering leadership and organizational innovativeness. Depending upon the resource-based view theory, this study comprehensively investigates the sequential effects of empowered leadership on the mediating roles of organizational identification and intellectual capital in organizational innovativeness.

Data were gathered through a self-administered questionnaire, which got 337 responses from telecom employees. To evaluate the hypotheses, the data were analyzed in SEM-M-Plus using exploratory and confirmatory factor analyses.

The findings demonstrate that empowering leadership impacts organizational innovativeness with the sequential mediation of organizational identification and intellectual capital (structural, human and social).

Organizations can identify and encourage leaders who exhibit empowering behaviors such as delegating responsibilities, providing autonomy and fostering a sense of ownership among employees. Also, organizations can foster intellectual capital by providing opportunities for learning, training and development. Additionally, knowledge sharing and collaboration can help to enhance the intellectual capital of employees.

While much research has been conducted on empowering leadership, the continued development of knowledge and the emergence of new perspectives related to identification and intellectual capital highlights the importance of exploring alternative paths that have been overlooked. Therefore, there is a pressing need to conduct research that takes into account these additional factors.

This paper aims to explore the key elements and dynamic formation mechanisms involved in the company identity construction during multicompany identification.

This study adopted a longitudinal single case study method, selected a representative company as the study case and analyzed the interactive practice of identity construction between the company and its external stakeholders based on the theory of organizational identity and sensemaking.

This study finds that the process of company identity construction for external stakeholders involves six elements. Companies mainly use a highly controlled, equality and interaction model to develop identity for a single stakeholder. Company identity is based on the company’s core identity claims and is formed by gradually integrating and cooperating with the identity claims of different stakeholders. Meeting the self-defining needs of stakeholders is a key driving force behind the evolution of company identity.

This study offers practical implications for companies to pursue and construct multicompany identity. For different types of external stakeholders, companies can adopt different identity sensemaking models. To build a new company identity, a company needs to do more on the basis of identity insights to break cognitive constraints and build new identity claim. Companies need to integrate new identity claims with the original identity claims. If different identity claims conflict or are difficult to reconcile, it may damage their original identity claims and companies need to evaluate the trade-offs.

This study expands the concept of company identity construction from the individual perspective to organizational identity and contributes to research in relationship marketing. This study identifies the key elements of company identity construction with multistakeholder participation and contributes to theory building in company identity research. The results of this study reveal the company identity construction mechanism for different external stakeholders and the dynamic formation process of multicompany identity.

This study aims to explore how sustainable business models (SBM) can be developed within agri-innovation systems (AIS) and emphasize an integration of the two with a systemic understanding for reducing food loss and value loss in postharvest agri-food supply chain.

This study conducted longitudinal qualitative research in a developing country with food loss challenges in the postharvest supply chain. This study collected data through multiple rounds of fieldwork, interviews and focus groups over four years. Thematic analysis and “sensemaking” were used for inductive data analysis to generate rich contextual knowledge by drawing upon the lived realities of the agri-food supply chain actors.

First, this study finds that the value losses are varied in the supply chain, encompassing production value, intrinsic value, extrinsic value, market value, institutional value and future food value. This happens through two cumulative effects including multiplier losses, where losses in one model cascade into others, amplifying their impact and stacking losses, where the absence of data stacks or infrastructure pools hampers the realisation of food value. Thereafter, this study proposes four strategies for moving from the loss-incurring current business model to a networked SBM for mitigating losses. This emphasises the need to redefine ownership as stewardship, enable formal and informal beneficiary identification, strengthen value addition and build capacities for empowering communities to benefit from networked SBM with AIS initiatives. Finally, this study puts forth ten propositions for future research in aligning AIS with networked SBM.

This study contributes to understanding the interplay between AIS and SBM; emphasising the integration of the two to effectively address food loss challenges in the early stages of agri-food supply chains. The identified strategies and research propositions provide implications for researchers and practitioners seeking to accelerate sustainable practices for reducing food loss and waste in agri-food supply chains.

There is a growing need to promote and practice sustainable HRM to foster greener organizations with trained employees who have an attitude and behavior to preserve depleting resources. The purpose of this study is to highlight the importance of sustainable green human resource management (Green HRM) practices along with organizational identification (OI) as a mediating factor and perceived organizational support (POS) as a moderating factor.

Quantitative methodology was used, and the data were collected from 311 employees working in telecommunication organizations located in the twin cities of Rawalpindi and Islamabad, Pakistan. Results of the study are based on the structural equation modeling technique using Smart-PLS.

Findings revealed that OI proved to be a significant positive mediator between Green HRM and organizational citizenship behaviors for the environment. POS also proved to be a significant moderator on the relationship between Green HRM and OI.

The study is limited to the two cities of Pakistan; future studies can focus on more cities so that the results can be more generalized.

This study will especially be useful for HR practitioners to develop mechanisms to initiate and encourage sustainable HR practices.

Organizations’ positive position is established through the inculcation of green activities among their employees. Thus, a sense of responsibility and attachment among employees toward green behavior makes them good citizens. It also works well for their organization as well as for the environment. Moreover, it preserves environmental resources and helps ensure sustainability.

The research paper was aimed at exploring the importance of sustainable Green HRM practices in a developing country like Pakistan.

Industry 4.0 defines the application of digital technologies on business infrastructure and processes. With the increasing need to take into account the social and environmental impact of technologies, the concept of Society 5.0 has been proposed to restore the centrality of humans in the proper utilization of technology for the exploitation of innovation opportunities. Despite the identification of humans, resilience and sustainability as the key dimensions of Society 5.0, the definition of the key factors that can enable Innovation in the light of 5.0 principles has not been yet assessed.

An SLR, followed by a content analysis of results and a clustering of the main topics, is performed to (1) identify the key domains and dimensions of the Industry 5.0 paradigm; (2) understand their impact on Innovation 5.0; (3) discuss and reflect on the resulting implications for research, managerial practices and the policy-making process.

The findings allow the elaboration of a multileveled framework to redefine Innovation through the 5.0 paradigm by advancing the need to integrate ICT and technology (Industry 5.0) with the human-centric, social and knowledge-based dimensions (Society 5.0).

The study detects guidelines for managers, entrepreneurs and policy-makers in the adoption of effective strategies to promote human resources and knowledge management for the attainment of multiple innovation outcomes (from technological to data-driven and societal innovation).

Automatic modulation recognition (AMR) is a challenging problem in intelligent communication systems and has wide application prospects. At present, although many AMR methods based on deep learning have been proposed, the methods proposed by these works cannot be directly applied to the actual wireless communication scenario, because there are usually two kinds of dilemmas when recognizing the real modulated signal, namely, long sequence and noise. This paper aims to effectively process in-phase quadrature (IQ) sequences of very long signals interfered by noise.

This paper proposes a general model for a modulation classifier based on a two-layer nested structure of long short-term memory (LSTM) networks, called a two-layer nested structure (TLN)-LSTM, which exploits the time sensitivity of LSTM and the ability of the nested network structure to extract more features, and can achieve effective processing of ultra-long signal IQ sequences collected from real wireless communication scenarios that are interfered by noise.

Experimental results show that our proposed model has higher recognition accuracy for five types of modulation signals, including amplitude modulation, frequency modulation, gaussian minimum shift keying, quadrature phase shift keying and differential quadrature phase shift keying, collected from real wireless communication scenarios. The overall classification accuracy of the proposed model for these signals can reach 73.11%, compared with 40.84% for the baseline model. Moreover, this model can also achieve high classification performance for analog signals with the same modulation method in the public data set HKDD_AMC36.

At present, although many AMR methods based on deep learning have been proposed, these works are based on the model’s classification results of various modulated signals in the AMR public data set to evaluate the signal recognition performance of the proposed method rather than collecting real modulated signals for identification in actual wireless communication scenarios. The methods proposed in these works cannot be directly applied to actual wireless communication scenarios. Therefore, this paper proposes a new AMR method, dedicated to the effective processing of the collected ultra-long signal IQ sequences that are interfered by noise.

The purpose of this review paper was identifying barriers to the use of telemedicine systems in primary health-care individual level among professionals.

This study used Scopus and PubMed databases for scientific records identification. A systematic review of the literature structured by PRISMA guidelines was conducted on 37 included papers published between 2009 and 2019. A qualitative approach was used to synthesize insights into using telemedicine by primary care professionals.

Three barriers were identified and classified: system quality, data quality and service quality barriers. System complexity in terms of usability, system unreliability, security and privacy concerns, lack of integration and inflexibility of systems-in-use are related to system quality. Data quality barriers are data inaccuracy, data timeliness issues, data conciseness concerns and lack of data uniqueness. Finally, service reliability concerns, lack of technical support and lack of user training have been categorized as service quality barriers.

This review identified and mapped emerging themes of barriers to the use of telemedicine systems. This paper also through a new conceptualization of telemedicine use from perspectives of the primary care professionals contributes to informatics literature and system usage practices.

When evaluating the efficacy of mindfulness interventions, most studies take a linear approach to explore how an intervention impacts different outcomes for individuals, and rarely is the role of intention examined. This research takes a configural approach to consider how various elements of a participant’s training expectations and their experience in the training condition combine to predict increases in psychological capital.

Employees from hospital settings were randomized into three conditions (mindfulness training, active control (Pilates), and wait-list control group) and completed surveys at three time points (baseline, post-training and three months post-training). A qualitative comparative analysis was applied to see what combinations of motivational elements were associated with increases in psychological capital.

We find that all three conditions can boost their psychological capital based on different configurations involving efficacy beliefs, baseline states of well-being (psychological capital and perceived stress) and changes in levels of mindfulness and perceived stress.

Individual characteristics, like motivation, expectancy and baseline needs, are an important consideration in addition to the training condition itself when determining whether a training is efficacious.

It is of increasing importance that organizations find ways to support employee well-being. Offering a variety of psychological and physical interventions can improve psychological capital. Applying needs assessments that clarify the desires, needs and expectations employees hold may help with intervention efficacy.

The current study offers an innovative methodology through which realist evaluation approaches can consider multiple factors to predict outcomes.

The various quality improvement (QI) frameworks and maturity models described in the health services literature consider some aspects of QI while excluding others. This paper aims to present a concerted attempt to create a quality improvement maturity model (QIMM) derived from holistic principles underlying the successful implementation of system-wide QI programmes.

A hybrid methodology involving a systematic review (Phase 1) of over 270 empirical research articles and books developed the basis for the proposed QIMM. It was followed by expert interviews to refine the core constructs and ground the proposed QIMM in contemporary QI practice (Phase 2). The experts included academics in two academic conferences and 59 QI managers from the New Zealand health-care system. In-depth interviews were conducted with QI managers to ascertain their views on the QIMM and its applicability in their respective health organisations (HOs).

The QIMM consists of four dimensions of organisational maturity, namely, strategic, process, supply chain and philosophical maturity. These dimensions progress through six stages, namely, identification, ad-hoc, formal, process-driven, optimised enterprise and finally a way of life. The application of the QIMM by the QI managers revealed that the scope of QI and the breadth of the principles adopted by the QI managers and their HOs in New Zealand is limited.

The importance of QI in health systems cannot be overstated. The proposed QIMM can help HOs diagnose their current state and provide a guide to action achieving a desirable state of quality improvement maturity. This QIMM avoids reliance on any single QI methodology. HOs – using the QIMM – should retain full control over the process of selecting any QI methodology or may even cherry-pick principles to suit their needs as long as they understand and appreciate the true nature and scope of quality overstated. The proposed QIMM can help HOs diagnose their current state and provide a guide to action achieving a desirable state of quality improvement maturity. This QIMM avoids reliance on any single QI methodology. HOs – using the QIMM – should retain full control over the process of selecting any QI methodology or may even cherry-pick principles to suit their needs as long as they understand and appreciate the true nature and scope of quality.

This paper contributes new knowledge by presenting a maturity model with an integrated set of quality principles for HOs and their extended supply networks.