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A technique in which the features of retinal receptors, receptive fields of the peripheral cells and cortical retinotopic mapping can be combined to perform a template matching system requiring a single reference pattern has been devised for artificial vision algorithms.

The current era is characterized by hyperturbulence, population growth, attention to food security, the need to identify sustainable strategies to reduce pollution and poverty, and the disparity between developed and undeveloped economies. These circumstances force a global paradigm shift based on sustainable practices and processes that put people and the environment at the core of each activity, contributing to sustainable, social, and economic development and promoting well-being in the community.

In this spirit, a strong impulse can derive from the practices of Green Technology, considered here as that set of processes aimed at eco-sustainability that acquire undisputed relevance, especially for emerging economies.

This chapter focuses on the role that Green technology practices exert in generating local well-being in the world's fifth-largest country: Brazil. Dynamic growth and effective social policies lifted millions of people out of poverty in the 2000s, even if socio-economic development varies widely across the country. Brazil is a leading global agricultural, minerals, and oil producer. The natural environment represents the primary source of Brazil's development that deserves to be protected and push firms and citizens to find new sustainable solutions based on green policies. Drawing inspiration from a Brazilian case study, this chapter proposes a set of building blocks that foster sustainable business practices in emerging countries.

The chapter is organized as follows: the first part introduces the concept of green technology practices; the second highlights the opportunities of green technologies; the third focuses on a single case study.

The 2030 Agenda for Sustainable Development underscores eradicating global poverty (Goal#1) and empowering women and girls (Goal#5) to foster sustainable, inclusive communities (Goal#11). The World Bank recognises female entrepreneurship as a catalyst for global economic growth, poverty reduction and gender equity. This chapter delves into the challenges hindering female entrepreneurship, obstructing poverty alleviation and community sustainability efforts worldwide. Public–private collaborations are crucial to support women in launching start-ups, adopting new technologies, enhancing digital skills and accessing financing in the era of Industry 4.0.

Our focus is on women entrepreneurship in BRICS nations due to their diverse growth trajectories and global economic significance. Employing a qualitative approach, we analyse public and private initiatives promoting female entrepreneurship in BRICS countries. Our findings highlight both commonalities and distinctions in their strategies and policies, implicitly contributing to poverty reduction and social and economic growth. This chapter not only identifies barriers faced by women entrepreneurs but also underscores factors fuelling their ventures. It offers a practical toolkit for scholars, policymakers and practitioners (entrepreneurs and consultants) to devise tailored strategies and actions for local growth and intervention. The study comprises four parts: the introduction, setting the chapter's goal and previewing outcomes; the second part, exploring female entrepreneurship as a key to poverty alleviation and community sustainability; the core, the third part, unveiling in-depth BRICS country analysis; and the conclusion, summarising implications and highlighting avenues for further research.

This paper sets out to design hyperbox classifiers of high interpretation capabilities. They are based on a collection of hyperboxes – generic and highly interpretable geometric descriptors of data belonging to a certain class. Such hyperboxes directly translate into conditional statements (rules) taking on the well‐known format “if feature₁ assumes values in [a,b] and feature₂ assumes values in [d,f] and … and feature_n assumes values in [w,z] then class ω” where the intervals ([a,b],…[w,z]) are the respective edges (features) of the corresponding hyperbox.

The proposed design process of hyperboxes consists of two main phases. In the first phase, a collection of “seeds” of the hyperboxes is constructed through data clustering being realized by means of the fuzzy C‐means algorithm. During the second phase, the hyperboxes are “grown” (expanded) by applying mechanisms of genetic optimization (and genetic algorithm, in particular).

It is demonstrated how the underlying geometry of the hyperboxes supports an immediate interpretation of arrhythmia data by linking the ranges of the features (parameters of the ECG signal) forming the edges of the hyperboxes with the two classes of the signals (normal – abnormal). A collection of comprehensive experiments offers an interesting insight into the geometry of the individual categories of the ECG signals and discusses how the resulting hyperbox classifiers link their geometric properties with the obtained classification rates.

The structure of the classifier is essential to enhance interpretation capabilities of the architecture and generate a collection of “if‐then” classification rules.

The study addresses an issue of design of highly interpretable, granular classifiers with the use of the technology of computational intelligence and evolutionary optimization, in particular.

This paper presents new approach to the integration of neural classifiers. Typically only the best trained network is chosen, while the rest is discarded. However, combining the trained networks helps to integrate the knowledge acquired by the component classifiers and in this way improves the accuracy of the final classification. The aim of the research is to develop and compare the methods of combining neural classifiers of the heart beat recognition.

Two methods of integration of the results of individual classifiers are proposed. One is based on the statistical reliability of post‐processing performance on the trained data and the second uses the least mean square method in adjusting the weights of the weighted voting integrating network.

The experimental results of the recognition of six types of arrhythmias and normal sinus rhythm have shown that the performance of individual classifiers could be improved significantly by the integration proposed in this paper.

The presented application should be regarded as the first step in the direction of automatic recognition of the heart rhythms on the basis of the registered ECG waveforms.

The results mean that instead of designing one high performance classifier one can build a number of classifiers, each of not superb performance. The appropriate combination of them may produce a performance of much higher quality.

The purpose of this paper is to integrate business process management (BPM) and accounting on a conceptual level in order to account for the economic implications of process-state changes in process design-time and process run-time.

The paper adopts a design science research paradigm. The research, grounded in an “events” approach to accounting theory, builds on the REA accounting model that has been adapted for the design of a process accounting model (PAM).

The paper presents a PAM that can be used to structure event records in process-aware information systems (PAIS) to enable process-oriented accounting. The PAM is specified as a light weight data structure that is intended for the integration of PAIS and accounting information systems.

As this paper is technical in nature, more research is needed to evaluate more thoroughly its approach in naturalistic settings.

The PAM can support traditional accounting approaches, and because of the adopted events approach, it readily supports use cases related to real-time analytics in BPM and accounting.

The PAM presents a novel approach to integrating BPM and accounting. The novelty of this approach lies in its use of event records to document flows of economic resources.

This paper uses dialectical inquiry to explore tensions that arise when adopting Industry 4.0 technologies in a lean production system and their reconciliation mechanisms.

We conducted an in-depth qualitative case study over a 3-year period on an Italian division of an international electrotechnical organisation that produces electrical switches. This organisation successfully adopted Industry 4.0 technologies in a lean production system. The study is based on primary data such as observations and semi-structured interviews, along with secondary data.

We identify four empirically validated dialectic tensions arising across different Industry 4.0 adoption stages due to managers’ and workers’ contrasting interpretations of technologies. Consequently, we define the related reconciliation mechanisms that allow the effective adoption of various Industry 4.0 technologies to support a lean production system.

This is the first empirical investigation of tensions in the adoption of Industry 4.0 technologies in a lean production system. Furthermore, the paper presents four theoretical propositions and a conceptual model describing which tensions arise during the adoption of Industry 4.0 technologies in a lean production system and the reconciliation mechanisms that prevent lean production system deterioration.

The purpose of this study is to explore how Industry 4.0 (I40) technologies support workers' engagement in soft total quality management (TQM) practices for organisational performance.

The authors conducted a multiple case study of six Italian manufacturing organisations that operate with I40 production and implement TQM practices. The authors concentrated on the relationship between I40 technologies and soft TQM aspects.

I40 technologies provide two forms of engagement with workers. Workers can act as machine supervisors and expert assembly operators. Organisations use five soft TQM practices to involve and develop workers for TQM that vary according to automation levels. The five soft TQM practices are top management design around workers, incremental trials with I40 technologies, worker empowerment, I40 sociotechnical collaboration and individual feedback systems.

In the literature that focusses primarily on how I40 technologies support the hard side of TQM by creating a data-driven and automated quality management system, the authors illustrate how the workforce can be engaged in I40 with five soft TQM practices to improve organisational performance. Thus, the authors complement the theory of hard and soft TQM aspects for I40 production systems.

In this regard, this paper aims to wonder how willing to co-create sustainable practices customers of irresponsible Industry 4.0 (I4.0) companies are? With this purpose, the authors began introducing I4.0 and sustainability, showing their theoretical gaps.

I4.0 has recently spread with its technological developments and social, economic and political ambitions, facing challenges-related, for example, to the implementation of sustainable practices and the stakeholders’ participation.

Then the authors conduct a literature review following a sequential mix-method approach that begins with a bibliometric analysis and ends with a content study to propose a conceptual model for I4.0 and sustainability. Once the authors understood the theoretical gaps in the framework of the conceptual model, the authors conducted an empirical verification between clients of a Colombian company of the I4.0 belonging to the logistic sector, specifically of the deliveries, asking them about the labor issues that the company faces with delivery people and their willingness to co-create. The authors analyzed the collected data through a structural equation modeling model, where the authors found that customers’ willingness to co-create depends on intrinsic behaviors like “responsible behavior,” followed by extrinsic behaviors such as “helping.”

In fact, stakeholders may support companies, but customers must learn how to assume a critical posture during their purchase decision.

This study aims to provide an overall framework that connects and explains a macro-perspective of the findings from the five studies of this special issue. Through this, we aim to answer two main questions: How can Lean and Industry 4.0 be integrated, and what are the outcomes for workers from such integration?

The special issue received 64 papers that were evaluated in multiple stages until this final sample of five papers that describe different facets of the integration between Lean and Industry 4.0 and their relationship with worker activities. In this introduction, we review the main findings of these five studies and propose an integrative view and associated propositions. A discussion provides directions to advance the field further.

The framework shows that when Lean and Industry 4.0 are integrated, companies will face two types of tensions, dialectical and paradoxical, which require different managerial approaches. By managing such tensions, the Lean-Industry 4.0 integration can help improve social performance, as well as develop systematic problem-solving and cumulative learning capabilities. Five important themes for this field of research are outlined: the importance of work routines, legitimation, competence, sense and mental flexibility.

This study brings a new theoretical perspective to the integration of Lean with Industry 4.0-related digital technologies. The results go beyond the usual view of improving operational performance and dig into the effects on workers. It also shows that the integration process relies on and can enhance human capabilities such as learning and problem-solving.