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The purpose of this paper is to carry out a theoretical study of the stability of the mathematical models defined in a class of systems. Furthermore, it will be supposed that the models have been obtained from experimental data and by means of the application of a methodology. The studies carried out in this paper are, on one hand, the theoretical framework for an analysis of the sensitivity and stability of a type of systems; on the other hand, they supplement the studies carried out by the authors, in which, using a computational program, the sensitivity of the mathematical models is analyzed with respect to a type of perturbation.

Initially, a class of systems is considered that are denominated quantifiable systems, in which model systems are defined that are determined by a set and a family of relationships. An initial study of the sensitivity of the mathematical models to perturbations in the experimental data lead to a concept of sensitive and stable models that forms the basis of the theory of stability developed in this paper. Furthermore, this permits a definition of the stability function for the set of the perturbations and, consequently, a determination of stable models according to the defined theoretical structure.

An analysis of the sensitivity and stability of mathematical models in quantifiable systems from a systems theory perspective will be fundamental for the determination of mathematical model stability in environmental systems.

The studies carried out in this paper supposes an advance in the study and modeling of a type of systems that the authors have denominated as quantifiable systems, applicable to the study of environmental systems and supplementing the numeric studies carried out by the authors.

A systematic study of a lotus's leaf area is described through the genetic improvement of Lotus glaber, an induced tetraploid population known as, Leonel, was obtained. Initial assessment showed an increase in dry material in comparison with a diploid population. The aim was to evaluate whether the increased production of forage found in the tetraploid population Leonel was due to increased foliolae sizes.

Three populations were studied L. glaber: diploid cytotype: seeds from a naturalised population of La Pampa Deprimida (Azul, Argentina); Tetraploid cytotype C1 seeds from the Leonel population, and Lotus corniculatus (Italia) seeds from Italy. Analysis of variance was carried out with a random design using a single factor, for the variables of area, length and width of the central foliolae. Linear and non‐linear model families were determined to estimate the area of the central foliolae. The selection criteria applied were: the best R², good efficiency, the greatest simplicity of the model and its stability.

The widths of the L. glaber diploid foliolae were less than those of L. corniculatus tetraploide and these were longer. The areas of the L. glaber foliolae were greater than those of the tetraploid L. corniculatus, and the areas of the foliolae of the diploid cytotype were slightly superior to the induced tetraploid cytotype L. Leoner. The best model was that which estimated the area of the central foliolae according to their width.

Non‐destructive estimates of foliar area were obtained for different species of the Lotus genus. The methodology chose provides a useful example of a systemic approach.

The variables studied are significant morphophysiological characteristics that can be used in programmes for the genetic improvement of L. glaber and L. corniculatus.

From the perspective of business history, this chapter presents an overview of the development of the tourism sector in South America, placing special emphasis on the Peruvian case. The chapter explores various topics related to the tourism chain, such as hotel networks, the role of the state, tour operators, micro- and small enterprises, linkages between tourism and sustainability, the formation of clusters in the sector, and interactions between different entrepreneurs in the chain. Special emphasis is placed on the Peruvian case, especially when it comes to discussing the role of micro- and small enterprises in the sector.

A third-order discrete time sigma delta modulator (SDM) is proposed with optimum performance by addressing instability and power dissipations issues, and a novel SDM architecture is designed and verified in behavioural modelling in MATLAB/SIMULINK environment. Simulation results show that performance parameters of proposed modulator achieved SNR of 105.41 dB, SNDR of 101.96 dB and DR of 17 bits for the signal bandwidth of 20 kHz.

This paper describes single-loop SDM design with optimum selection of integrator weights for physiological signal processing in IoT applications.

The proposed discrete time modulator designed with 1-bit quantizer and optimum oversampling ratio proved as power efficient. Integrator scaling coefficients are generated in LabVIEW environment for pure third-order noise shaping.

This paper contains the novelty in the work, and it is suitable for cognitive Internet of Things applications.

Educational Robotics is a research field aimed at promoting an active engaging learning through the artifacts students create and the phenomena they simulate. In fact, designing, building, and programming a small robot, users discover and learn in a playful and joyful way. Moreover, the constructivist approach fosters the development of creative and critical skills, as well as problem-solving, communication skills, cooperation, and teamwork. This chapter presents the results of a research with university students, carried out at the Università della Calabria (Italy): an Educational Robotics laboratory has been integrated in a Cognitive Psychology Course in order to examine the kind of learning, workgroup retention, and engagement. Outcomes show that engaging experiences can remarkably enhance students’ learning efficiency and retention of the acquired materials. Moreover, a rich interaction can provide entertaining and appealing experiences capable of promoting learning and understanding.

Despite the sizable amount of previous research on this topic, little is known about the reasons why firms decide to start collaboration projects with innovation advanced service providers, such as universities and technological institutes. This paper aims to investigate which factors at an individual firm level are involved in these collaborative strategies on supporting product and management improvements offered by local institutions to innovative firms.

The research is contextualized in the Valencian region and applies the resource based view and the regional innovation system approach as theoretical frameworks. Methodologically, the paper adopts a cross‐sectional analysis and employs ordered regression models on a sample of innovative firms during 2009.

Firstly, this paper endorses previous research suggesting the crucial role of cooperation and external knowledge on SME innovation. Secondly, it evidences how internal resources and capabilities determine a firm's use of public supported innovation. Thirdly, previous experience appears to be extremely relevant in explaining successful engagement in both technological and managerial innovation programs.

Because the case study approach and qualitative methodologies are used, the authors advise readers not to generalize their findings. The research on the subject matter is offered as a means to substantiate or refute the latest research premises, and provide empirical evidence on the selected region.

Although this paper corroborates recent contributions, it does provide some novel findings. High‐level managerial capabilities seem to discourage the use of public programs supporting innovation practices (either in technological or managerial aspects), while engagement in university programs relies heavily on the firm's technological capabilities or exposure to global competition, and less on other characteristics. Policy makers should pay particular attention to both pieces of evidence when designing programs.

This study aims to analyse the provision of knowledge‐intensive services (KIS) by technology centres based on approaches used in the literature on trade areas.

The techniques employed derive from the literature on trade areas (customer spotting and ring studies) and spatial analysis (nearest neighbour analysis, Ripley's K statistic and median centre).

The research demonstrates that there is a geographic factor in the distribution of firms associated with a technology centre and some of their characteristics depend on their proximity to such a centre. Trade areas are determined and access facilities are detected. It has also been observed how geographic proximity is coupled with functional (sector) factors in the firm‐technology centre relationship.

These findings may contribute towards strategies for locating technology centres, and may be extended to future centre networks and to the development of more efficient marketing strategies aimed at attracting and acquiring client firms.

To date, little is known about the spatial distribution of firms associated with technology centres, nor are there studies that relate the profile of user firms in relation to the distance from their premises to the technology centre. Using methodology previously applied to trade areas, this research has identified the spatial pattern of associated firms which may be of use for a variety of purposes.

The purpose of this paper is to: first, divide external knowledge into different levels and understand how these different levels of external knowledge create different knowledge networks. Second, explore the relation among different levels of external knowledge, different types of knowledge and their influences on innovation. Different types of knowledge may act as mediators between different levels of external knowledge and innovation performance are also discussed. Third, further explicate the possible reasons behind the phenomena observed in the first and second objectives.

The quantitative and qualitative research methods were adopted in this study. In terms of the quantitative research method, data were collected from 157 information and communications technology (ICT) companies in Zhangjiang. There were 38 interviews carried out using the qualitative research method. Interviewees included 26 directors from the Zhangjiang ICT chip companies and 12 directors from China’s domestic mobile phone manufacturing sector.

This study finds out that the source of external knowledge in the Zhangjiang Hi-Tech Park is mostly derived from cross-regional and cross-national connections. Through the connection with global companies, the firms in Zhangjiang acquire technical knowledge. Also, through the interaction with cross-regional companies, the firms in Zhangjiang absorb market knowledge. The results of this study indicate that the cross-regional connections are spurred by the increasing demand of the Chinese domestic market and the government’s support for cross-regional interactions. Cross-national connections are encouraged and led by the Chinese Government after China’s 3G communication standard is adopted.

This study is built upon a case study in Zhangjiang of China. The findings of this study may not be applicable to other countries or regions in China. Also, this study only focusses on the ICT industry in Zhangjiang. Knowledge from different industries is not included in this study. In addition, the formal and informal knowledge flow is neglected in this study as well.

The findings of this study provide business executives and policymakers with a new way of thinking about the development of industrial clusters and local firms. Firms may be able to find new ways to raise innovation performance using different external knowledge.

The major contribution of this study is an initial attempt to provide a comprehensive analysis of external knowledge of industrial clusters, different types of knowledge and their influences on innovation performance. Moreover, the mediating effects of different types of knowledge are also discussed.

The aim of this paper is to present design management as a dynamic capability and to analyze its mediating role between organizational learning capability and product innovation performance in small and medium enterprises (SMEs).

Structural equation modeling is used to test the research hypotheses based on data from the Italian and Spanish ceramic tile industries. The data are derived from the responses of 182 companies (50 percent of the target population) to a questionnaire addressed to Product Development Managers and Human Resource Managers.

The results suggest that organizational learning capability enhances product innovation through the mediation of design management capability. The authors find an interesting interplay between organizational learning, design management capability and product innovation that can be very useful to better understand how to improve innovation performance. This finding shows that design management, as a dynamic capability, emerges from learning and allows the firm to adapt to environmental changes.

Several works have studied dynamic capabilities but without specifying the nature of these capabilities. More recent empirically‐based studies conceptualize and refer to specific dynamic capabilities. In this paper, the authors present design management as a dynamic capability. This study aims also to develop a better understanding of how organizational learning capability impacts on the product innovation performance of SMEs and how this relationship is mediated by design management capability.

The COVID-19 pandemic has caused widespread disruptions to global industries, with the textile sector in South Asia being particularly hard hit. While previous studies have focused on the performance of textile sectors in individual countries, there is a gap in the literature on the comparative impact of the pandemic on the textile industry in South Asian nations. This study aims to fill this gap by investigating the performance of the textile sector in South Asian countries and identifying best practices for overcoming the pandemic’s adverse effects.

Using a comparative approach, this study analyzes the impact of COVID-19 on the performance of the textile sector in Pakistan, India and Bangladesh.

Our findings reveal that COVID-19 significantly negatively impacts the textile industry in Pakistan and India. However, Bangladesh has shown effective practices to support the textile industry and mitigate the pandemic’s adverse effects.

The findings of this study hold considerable implications for legislators, leaders, investors and supply chain management professionals operating within the South Asian textile sector. This research has the potential to inform policymakers in formulating strategies to facilitate the textile sector’s resilience during emergencies like the COVID-19 pandemic.

This paper provides significant theoretical additions to the current body of literature regarding the impact of COVID-19 on the textile sector in South Asia. The research uses the global value chain (GVC) theory as a theoretical framework to enhance understanding of the impact of global supply chains and interdependencies on the textile sector in the region.