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The application of condition-based maintenance on selected equipment can allow online monitoring using fixed, half-fixed or portable sensors. The collected data not always allow a straightforward interpretation and many false alarms can happen. The paper aims to discuss these issues.

Statistical techniques can be used to perform early failure detection. With the application of Cumulative Sum (CUSUM) Modified Charts and the Exponentially Weighted Moving Average (EWMA) Charts, special causes of variation can be detected online and during the equipment functioning. Before applying these methods, it is important to check data for independence. When the independence condition is not verified, data should be modeled with an ARIMA (p, d, q) model. Parameters estimation is obtained using the Shewhart Traditional Charts.

With data monitoring and statistical methods, it is possible to detect any system or equipment failure trend, so that we can act at the right time to avoid catastrophic failures.

In this work, an electro pump condition is monitored. Through this process, an anomaly and four stages of aggravation are forced, and the CUSUM and EWMA modified control charts are applied to test an online equipment monitoring. When the detection occurs, the methodology will have rules to define the degree of intervention.

We present a critical literature review debating Brazilian research on social and environmental accounting (SEA). The aim of this study is to understand the role of politics in the construction of hegemonies in SEA research in Brazil. In particular, we examine the role of hegemony in relation to the co-option of SEA literature and sustainability in the Brazilian context by the logic of development for economic growth in emerging economies. The methodological approach adopts a post-structural perspective that reflects Laclau and Mouffe’s discourse theory. The study employs a hermeneutical, rhetorical approach to understand and classify 352 Brazilian research articles on SEA. We employ Brown and Fraser’s (2006) categorizations of SEA literature to help in our analysis: the business case, the stakeholder–accountability approach, and the critical case. We argue that the business case is prominent in Brazilian studies. Second-stage analysis suggests that the major themes under discussion include measurement, consulting, and descriptive approach. We argue that these themes illustrate the degree of influence of the hegemonic politics relevant to emerging economics, as these themes predominantly concern economic growth and a capitalist context. This paper discusses trends and practices in the Brazilian literature on SEA and argues that the focus means that SEA avoids critical debates of the role of capitalist logics in an emerging economy concerning sustainability. We urge the Brazilian academy to understand the implications of its reifying agenda and engage, counter-hegemonically, in a social and political agenda beyond the hegemonic support of a particular set of capitalist interests.

The purpose of this paper is to comprehensively and accurately analyze the supply and demand structural balance of grain in the context of China's agricultural supply-side reform. By subdividing and forecasting the supply and demand, it is beneficial for targeted production in the case of clear demand and supply trends of main grain varieties.

This paper forecasted and analyzed the demand of main grain varieties by the grey interval forecast, and based on the grey incidence analysis of more influence factors, forecasted the grain production with GM (1,N) model.

The results show that the demand and yield will keep sustainable growth in the next three years, while there is still a big gap between the supply and demand of the main grain varieties in China and the soybean's production is far behind the growing demand.

This paper can make full use of the information to provide the evidence for government to formulate policies and put forward some correlative suggestions for growers.

In this paper, the grey model technology is applied to the structural reform of grain supply side, and different models are used to predict the structural balance of supply and demand of different kinds of grain. The study of grain supply and demand structural balance in China is vital to ensure grain security in the context of agricultural supply-side reform.

Despite the positive effects of customer capital (CC), questions remain over how managers enable CC growth by applying their skills and capabilities through managerial actions and strategies, such as developing information technology (IT) capability, fostering relationship learning (RL) activities and developing green innovation performance (GIP) with clients. These questions are especially pertinent in small and medium-sized enterprises and automotive industry companies that operate through supply chains, where knowledge about customers is likely to result from personal contact between customers and organisational members. The purpose of this paper is to analyse the extent to which these managerial actions were more likely to lead to the successful creation of CC.

Using the partial least squares technique, this paper studies how these three managerial actions impact on CC. To do so, data from 140 companies in the Spanish automotive components manufacturing sector have been used.

The findings support the influence of RL on both GIP and CC. RL is a key managerial action in exploiting customer information and knowledge advantages, enabling firms to structure and reconfigure resources to produce new ways to compete and to satisfy stakeholders. In addition, results show that GIP is a determinant of CC because of its contribution to achieving sustainable competitive advantage, with GIP performing a mediating role in the relationship between RL and CC. A second contribution shows that IT is not in itself able to yield a competitive advantage, thereby validating the existence of complementary or co-focused strategic assets such as RL and GIP, which enhance IT’s influence on CC.

The authors were unable to explore the subtleties of the processes over time. Future research should include a longitudinal study.

This study considers RL an essential factor in achieving both GIP and CC. Consequently, managers should seek to build strong RL cultures. In addition, this study shows that IT is not in itself able to yield a competitive advantage, thereby validating the existence of complementary or co-focused strategic assets such as RL and GIP.

No study has ever examined these three antecedent variables (IT, RL and GIP) together, with the aim to examine their effects on CC.

The purpose is to create an algorithm that optimizes the trajectories that an autonomous vehicle must follow to reduce its energy consumption and reduce the emission of greenhouse gases.

An algorithm is presented that respects the dynamic constraints of the robot, including the characteristics of power delivery by the motor, the behaviour of the tires and the basic inertial parameters. Using quadratic sequential programming with distributed and non-monotonous search direction (Quadratic Programming Algorithm with Distributed and Non-Monotone Line Search), an optimization algorithm proposed and developed by Professor K. Schittkowski is implemented.

Relations between important operating variables have been obtained, such as the evolution of the autonomous vehicle’s velocity, the driving torque supplied by the engine and the forces acting on the tires. In a subsequent analysis, the aim is to analyse the relationship between trajectory made and energy consumed and calculate the reduction of greenhouse gas emissions. Also this method has been checked against another different methodology commented on in the references.

The main limitation comes from the modelling that has been done. As greater is the mechanical systems analysed, more simplifying hypotheses should be introduced to solve the corresponding equations with the current computers. However, the solutions are obtained and they can be used qualitatively to draw conclusions.

One main objective is to obtain guidelines to reduce greenhouse gas emissions by reducing energy consumption in the realization of autonomous vehicles’ trajectories. The first step to achieve that is to obtain a good model of the autonomous vehicle that takes into account not only its kinematics but also its dynamic properties, and to propose an optimization process that allows to minimize the energy consumed. In this paper, important relationships between work variables have been obtained.

The idea is to be friendly with nature and the environment. This algorithm can help by reducing an instance of greenhouse gases.

Originality comes from the fact that we not only look for the autonomous vehicle’s modelling, the simulation of its motion and the analysis of its working parameters, but also try to obtain from its working those guidelines that are useful to reduce the energy consumed and the contamination capability of these autonomous vehicles or car-like robots.

This study aimed to assess whether sociodemographic variables explain significant differences in attitudes towards transforming academic conferences into more sustainable events.

An analytical model of participants' attitudes towards sustainable conferences based on literature review as well as the theories of reasoned action and planned behaviour was developed and applied to a sample of 532 surveyed individuals from 68 countries who regularly attended academic conferences in the last five years prior to 2020. The results were refined using statistical and computational techniques to achieve more empirically robust conclusions.

Results reveal that sociodemographic variables such as attendees' gender and age explain differences in attitudes. Women and older adults have stronger pro-environmental attitudes regarding event sustainability. On the other hand, attitudes towards more sustainable academic conferences are quite strong and positive overall. More sustainable events' venues, catering, conference materials and accommodations strongly influence attendees' attitudes towards more sustainable conferences. The strength of attitudes was weaker towards transportation.

First, the analyses focused on only aspects related to the attendees' attitudes. Assessing their real behaviour would complete this research. The geographical areas defined by the U.N. and used in this study have the limitation of combining highly developed countries and developing countries in the same geographical area, for example, the Americas and Asia and the Pacific.

Specific socio-demographic variables' effects on attitudes towards sustainable academic conferences can indicate how organisers can best promote these events according to attendees' characteristics and develop differentiated marketing campaigns. For women and older adults, event sustainability should be emphasised as a competitive strategy to promote events and attract these audiences. Marketing strategies for younger attendees (under 30 years old) could focus on technology, networking or attractive social programmes. Sustainable venues, catering, conference materials and accommodations are easier to promote. Event organisers should encourage participants to make more environmentally friendly decisions regarding more sustainable event transport.

A strategy based on promoting the event as contributing to sustainable development could educate attendees and put them on the path to developing stronger positive attitudes regarding sustainability and more sustainable behaviours. Sustainable academic conferences can educate students, organisers, service providers and delegates through their involvement in sustainable practices.

To our best knowledge, this research is the first to assess whether sociodemographic variables explain significant differences in attitudes towards the sustainable transformation of academic conferences.

Training as an important source of dynamic capabilities (DC) is important to the performance of sports’ organisations (SO) both to athletes and to non-athletic staff. There are a variety of training delivery methods (TDMs). The purpose of this study is to determine from a set of six TDMs which one is considered to be the most suitable to enhance performance of SO.

Based on the DC theory, a cross-sectional survey from a sample of 554 workers was used to assess which TDM is considered to be the most efficient and presents higher efficacy, according to the preferences and perception of the staff.

It was concluded that: “on-the-job training” is considered to be the preferred and most effective TDM; formal/informal coaching is the second choice, in terms of perceived effectiveness and “online learning” is considered the least effective TDM. TDM’s preferences and results’ perceptions do not change according to differentiating issues such as gender, educational level of trainees or even hierarchical position.

The present study adopted a cross-sectional survey where relationships and correlations were developed continuously. Although difficult to obtain, it would have been advisable to use a survey based on longitudinal data. Results should only be considered for the purposes of the present sample, although it may be considered that they are generalizable to similar organisations and some preliminary results are raised that worth being analysed further.

The outcomes of this study will help managers of SO, according to the situation to be addressed, to choose the best TDM for their non-athletic staff, the ones that will best support their process of continuous improvement and show the best results in terms of renewal of their DC and resources.

This study highlights the training process as a source of DC contributing to overall organisation’s performance and competitive advantage. It enlarges knowledge on SO, from the pure athletic view to the managerial point of view, and operationalises training to decide the most adequate TDM to improve DC and support the success of SO. Considering that it is usually difficult to measure the concrete results of training on the organisational performance, this is also an important field of study for the management theory in the domain of strategy and human resources because the bridge considered here has not been much developed for a long time.

The purpose of this paper is to demonstrate mathematically the impossibility of achieving a utopian society. Demonstrate that any attempt to correct deviations from a hypothetical trajectory whose ultimate goal is the utopia, increasingly demands more work, including measures that lead to terror, which may even be absolute, leading to the horrible paradox that in seeking paradise hell is constructed.

Scientific tools that the authors have used are: the theory of the system linkage, alysidal algebra, kinematic theory and vector analysis.

Myths are the substrate of some complex systems of beliefs and utopia is its ultimate goal. The use of the combination of the theory of trajectories, belonging to the alysidal algebra, the theorem of unintended effects and kinematics theory provides an approximation to deviations suffering utopian ideological currents and their corrections.

This paper is a continuation of other previous papers developing the theory of complex societies.

The purpose of this paper is to investigate low-wage retention using a survival analysis approach.

Variables explaining low-wage retention take into account the characteristics of the employee, such as education, age, tenure with the company, gender and nationality, and the characteristics of the job and the company such as industry affiliation, number of employees, age of the company and location.

Female workers and workers with low level of education, older ones, those with more seniority in the company and those of Asian origin remain longer in a low-wage situation. Also, workers in smaller and older companies located outside the Lisbon region are more likely to stay in a low-wage situation.

The policy implications are clear. Education plays a prominent role: the higher the level of education of the individual, the higher the probability of him/her leaving low pay. Training programs may help employees in Portugal to leave the low-wage situation. Furthermore, policies must address the different mobility rates of different nationalities and different activities. Training programs are more urgent for hotels and restaurants and transports and communication. The findings also indicate that those initially working in younger firms and larger firms have a higher probability of leaving the low-wage situation. This is a stimulus for decision makers to stimulate employment in the younger firms or in the larger firms.

Despite low-wage retention being a well-known field of research, to our knowledge this is the first research paper using survival analysis to explain the duration of a low-wage situation.