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The football industry is a most unusual one. Football clubs, unlike most other organisations, need to cooperate in order to provide a saleable product, a game. Companies can only enter the industry with the specific approval of those already within, and this approval is rarely given since it leads to the expulsion of existing members. The industry requires that less successful clubs be cross‐subsidised and restricts the payment of directors' fees and dividends. Until 1981/2 a minimum admission price was also stipulated. Such supportive measures contrast sharply with the nature of competition on the field of play in which there can be ‘only one winner’. The pursuit of playing success as a dominant objective means that few can ‘succeed’ in any one season, whereas in industries in which orthodox financial objectives are important several firms may succeed simultaneously.

The substantial resources devoted to warfare in modern times might explain the increasing relevance that military spending has acquired in social sciences. In this regard, the so-called defence economics has extensively studied the main determinants of military spending and its main consequences in terms of economic performance and institutional transformations. However, one of the main problems for comparative analysis on the causes and effects of military spending is the lack of long-term homogeneous and comparable data in international panel datasets. This paper contributes to fill in this gap by providing new military spending data on Spain from 1850 to 2009 based on NATO methodological criterion. It provides total military spending estimates as well as economic and administrative disaggregated figures for most of the period. These data allow reliable international comparisons while also providing new quantitative evidence to better understand the military history of Spain in modern times.

This chapter presents a quantitative description of the living conditions in a slum area of an intermediate Argentinean city during the outburst of the Covid-19 crisis using primary data collected four months after the lockdown measures had been introduced. The sample represents 1,500 households which claimed food assistance over this period, and whose deprivations and presence of young members are similar to that of 13% of the city’s population and 23% of the country’s population. Rough estimates suggest a disproportionate drop in employment and a disproportionate increase in unemployment in the area compared to those registered in the aggregate of the main urban agglomerations of the country. Cash transfers implemented during the lockdown, together with in-kind food aid from schools, the municipal government, and the church with non-governmental organizations, entailed a substantial average increase in the coverage of the cost of the basic food basket. However, non-trivial fractions of households were not covered by any of the main cash transfers. Also, and despite efforts, food insecurity could not be avoided. Considering the similarity of the sample to significant fractions of the country’s urban population, the deprivations experienced over 2020 by groups which were already in poverty before the Covid-19 arrival, raise alarms on the future well-being of these populations, especially for infants and children. Novel policies are required, addressing the various critical needs in an interconnected way, integrating the different stakeholders that have proven to be key in assisting these households during such an unprecedented covariate shock.

This study attempts to quantify the loss of accuracy that arises after packaging and during the life of the IC device. To identify a solution to the problem of mismatch in voltage dividers, the characterisation of the amount of stress associated with commercially available moulding compounds was performed by means of silicon integrated strain gauges. In addition, the influence of the voltage divider lay‐out was measured with a specifically designed test pattern. The possibility of producing circuits with an accuracy level better than 0·1% without trimming was demonstrated.

Rosin‐modified polyesteramide resins are prepared covering a wide range of oil lengths by partial replacement of hydroxy ethyl fatty acid amides employed in resin formulations by rosin‐diethanolamine derivative without affecting the resin constants. This is followed by a study of the optimum amount of modifier which improve the resins performance and durability without affecting the other properties. Optimum modifier concentration and durability characteristics are then determined.

The purpose of this paper is to present a new service discovery protocol (SDP) suitable for wireless sensor networks (WSN). The constraints imposed by ultra low‐cost sensor and actuators devices (basic components of a WSN) are taken into account to minimize the overall footprint.

It is based on the lightweight WSN communication model used by picoObjects, a tiny implementation of the distributed object concept and the same design criteria are followed, aiming at minimal overhead for devices and communication protocols. In spite of its simplicity it is powerful enough to deploy a valuable set of services.

This approach provides a remote interface that client applications can use without knowing where the service is implemented (platform and location independence).

The future work is mainly focused on integrating third party services using different SDPs, making possible the real deployment of large heterogeneous pervasive environments.

Designers may change the underlying SDP model (e.g. centralized versus distributed) without affecting applications by just tweaking configuration settings.

Embedded devices can participate in the service discovering procedure providing their own services by means of standard distributed objects. Also, the protocol is suitable for any kind of dynamic networked system.

This paper aims to investigate a firm’s incentive to innovate its basic product to be socially responsible and its decision on the product line. By constructing a competition model, the paper examines the factors that affect the firm’s choice on its product line with the socially responsible innovation in the presence of altruistic consumers. Such factors include the proportion of the altruistic consumers, the firm’s coordination cost with the basic and innovative products, as well as the consumer’s transportation cost.

In a model of differentiated products with the competition, the author assumes that a portion of consumers has a strong preference for the socially responsible product (e.g. altruistic consumers). A firm is able to attract altruistic consumers with a socially responsible innovation but it may incur a coordination cost when both the basic and the innovated products are manufactured and sold. In a framework of a sequential game, the firms make a decision on the prices, innovation inputs, as well as the choice on its product line to achieve the expected profit maximization.

The firm has the incentive to engage in socially responsible innovation to better compete with its rivals. More importantly, the results of the paper explain why some firms wish to manufacture and sell the basic product even though the innovation is successful. The main factors that affect such a firm’s decision include the proportion of the altruistic consumers, the aggregate benefit to all the consumers who purchase the innovative product, the firm’s potential coordination cost and the consumer’s transportation cost.

The paper sheds light on a firm’s corporate social responsibility innovation and its product line determination. The results of this paper can be widely applied in the firm’s strategy of engaging in corporate social responsibility with eco-friendly elements that can attract altruistic consumers in the market. In addition, the findings of the paper can also contribute to policy formulation in terms of innovation. Such a result enables the policymakers to understand the factors that affect the firm’s motivation on innovation and helps them to better guide the firms efficiently participate in the research and development activities.

This study aims to design a femoral component with minimum volume and maximum safety coefficient. Total knee prosthesis is a well-established therapy in arthroplasty applications. And in particular, with respect to damaged or weakened cartilage, new prostheses are being manufactured from bio-materials which are compatible with the human body to replace these damages. A new universal method (design method requiring optimum volume and safety [DMROVAS]) was propounded to find the optimum design parameters of tibial component.

The design montage was analyzed via the finite element method (FEM). To ensure the stability of the prosthesis, the maximum stress angle and magnitude of the force on the knee were taken into consideration. In the analysis process, results revealed two different maximum stress areas which were supported by case reports in the literature. Variations of maximum stress, safety factor and weight were revealed by FEM analysis, and ANOVA was used to determine the F force percentage for each of the design parameters.

Optimal design parameter levels were chosen for the individual’s minimum weight. Stress maps were constructed to optimize design choices that enabled further enhancement of the design models. The safety factor variation (SFV) of 5.73 was obtained for the volume of 39,219 mL for a region which had maximum stress. At the same time, for a maximum SFV and at the same time an average weight, values of 37,308 mL and 5.8 for volume and SFV were attained, respectively, using statistical methods.

This proposed optimal design development method is new and one that can be used for many biomechanical products and universal industrial designs.

The objective of this research work is to study the artificial intelligence (AI)-based product benefits and problems of the agritech industry. The research variables were developed from the existing review of literature connecting to AI-based benefits and problems, and 90 samples of primary data from agritech industry managers were gathered using a survey of a well-structured research questionnaire. The statistical package of IBM-SPSS 21 was utilized to analyze the data using the statistical techniques of descriptive and inferential statistical analysis. Results show that better information for faster decision-making has been ranked as the topmost AI benefit. This implies that the executives of agritech units have a concern about the quality of decisions they make and resistance to change from employees and internal culture has been ranked as the topmost AI problem.