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The aim of this paper is to highlight the structure implemented in biological systems. Our modelling world view is based on automata and a hierarchical structure of biological system, because a feedback loop (the basic structure of any biological system) is a hierarchical structure, the processors of which are automata. Our modelling of a body metabolism (without energy production systems from lipids and proteins), is divided into two parts: Basic structure of a feedback loop and the structure of control of loops.

The purpose of this paper is to question the status of trade unions on corporate social responsibility (CSR) today in the European Union (EU). How do they go from being social partners to a full‐fledged stakeholder status? The paper examines this question both from the point of view of stakeholder theory and from a field study in three different European countries.

The methodology is qualitative, i.e. based on a series of face‐to‐face interviews conducted in three different European countries (France, Germany, the UK) with different stakeholders, union representatives, non‐governmental organizations, experts, employers' associations.

The main findings are: inadequacy between stakeholder theory and the reality of European trade unionism and the CSR debate; trade unions are not “natural” stakeholders, rather “stake‐seekers”; the national business approach is relevant, in that national differences account for major differences among the three countries studied; and the European and global implications of trade unions into CSR help them gain full stakeholder status.

The sample is a bit limited; it would be interesting to enlarge the scope of European countries. Also, it would also be relevant to interview shop‐floor members to analyze the gap between union officials and rank and file members.

This paper can help unions consider CSR in a better way, so as to integrate CSR issues into their agenda.

The status of trade unions in the CSR debate has largely been overlooked, whereas their role in European countries is quite important.

There has been very little previous research on trade unions and CSR. The cross‐cultural dimension of this research and the EU dimension add value to the paper.

SIXTH INTERNATIONAL CONGRESS OF CYBERNETICS AND SYSTEMS After London, Oxford, Bucharest, Amsterdam and Mexico, the triennal congress of the World Organisation of General Systems and Cybernetics (W.O.G.S.C.) took place in Paris (France) from 10 to 14 September 1984. It was organized by the College de Systemique of the Association Francaise pour la Cybernetique Economique et Technique (AFCET) at the Conservatoire National des Arts et Métiers (CNAM). It was sponsored by the Ministry of Research, CNAM, the Centre National d'Etude des Télécommunications, IBM‐France and Thomson.

This paper aims to investigate the effect of chronological age on the likelihood to choose a service provider with technological machines versus humans in the context of services.

Two experimental studies were used to collect data. In both experiments, scripts were devised to depict a food ordering situation. The studies, each of which represents two between-subject conditions, were presented to a total of 312 participants.

The results of studies show that as age increases, consumers show a higher visit likelihood with human servers as compared to self-ordering machines. This effect emerges because as age increases, people find it more comfortable and convenient to order from human servers. Nevertheless, when a self-ordering machine is the only option, older and younger people find it equally comfortable and convenient.

This research indicates that as age increases, consumers tend to choose human servers. However, age does not impact willingness to use technology when human service is not available. A limitation of our research is that we look at food ordering contexts only. Another limitation is that most participants were between 18 and 60 years of age.

With a better understanding of the effect of age on preference for service types and the reason behind it, this research helps implement and manage service technologies that may elicit favorable judgments and decisions from consumers.

It demonstrates how, when and why age affects the intention to visit service providers that adopt self-service technologies. This research suggests that as age increases, consumers like human service better, but they do not resist self-service technology.

Diversity – or having a range of different options – is an important part of being resilient. Yet research has not considered how diversity in terms of the governance relationship types that exist within a supply base or across a supply network relates to resilience. By drawing on a well-established global value chain (GVC) governance framework, this paper aims to investigate how different relationship governance types influence resilience at the dyadic and supply network level.

This research draws on 27 embedded cases of buyer-supplier relationships within a network, studied through 20 interviews in 11 organizations across four tiers of the Australian Defence Force supply network, including the end customer perspective, during and after a large-scale supply chain (SC) disruption. Analysis is conducted at the individual dyad and aggregated network levels.

At the dyadic buyer-supplier level, a variety of different resilience strategies and practices are used across the relationship governance types. Consequently, at the network level, relationships characterized by market and relational governance created more vulnerabilities during COVID-19 than hierarchical and modular governance relationships.

The GVC framework is extended to the SC domain, providing a deeper understanding of how GVC governance types in SC relationships relate to resilience strategies at the dyadic and network levels. Given that different governance relationships draw on different resilience strategies, diversity in governance relationships helps enhance overall resilience. Meanwhile, the findings show that resilience requires relational aspects to be considered alongside economic aspects of the GVC.

Product Lifecycle Management (PLM) systems have gained wide popularity for their role in manufacturing organizations for creating, managing and distributing product data. These systems are one of various enterprise systems which are required for smooth functioning and meeting the scaling up requirements organization. However, with introduction of cloud technology and other industry 4.0 initiatives, there has been focus on moving the on-premises IT application to the cloud. Such a move needs to be carried out by identifying and evaluating various challenges. This paper aims to discuss the aforementioned objective.

The challenges identified through literature review have also been confirmed to be present via interview, system observation and documentation review through case study-based validation in an automotive component manufacturing industry.

The article identifies needs and challenges of cloud PLM systems and presents a generic framework for developing an approach for cloud PLM journey for an organization. The article also provides an approach for resolving the different challenges to realizing the designed system.

The simplified generic framework has been presented for use by industry professionals and researchers for designing cloud PLM systems that would fulfill expectations of different levels of stakeholders.

The purpose of this paper is to identify corrosion types and corrosion transitions by a novel electrochemical noise analysis method based on Adaboost.

The corrosion behavior of Q235 steel was investigated in typical passivation, uniform corrosion and pitting solution by electrochemical noise. Nine feature parameters were extracted from the electrochemical noise data based on statistical analysis and shot noise theory. The feature parameters were analysis by Adaboost to train model and identify corrosion types. The trained Adaboost model was used to identify corrosion type transitions.

Adaboost algorithm can accurately identify the corrosion type, and the accuracy rate is 99.25%. The identification results of Adaboost for the corrosion type are consistent with corroded morphology analysis. Compared with other machine learning, Adaboost can identify corrosion types more accurately. For corrosion type transition, Adaboost can effectively identify the transition from passivation to uniform corrosion and from passivation to pitting corrosion consistent with corroded morphology analysis.

Adaboost is a suitable method for prediction of corrosion type and transitions. Adaboost can establish the classification model of metal corrosion, which can more conveniently and accurately explore the corrosion types. Adaboost provides important reference for corrosion prediction and protection.