Over the past couple of decades, Global positioning system (GPS) technology has been utilized to collect large-scale data from travel surveys. As the precise spatiotemporal characteristics of travel could be provided by GPS devices, the issues of traditional travel survey, such as misreporting and non-response, could be addressed. Considering the defects of dedicated GPS devices (e.g., need much money to buy devices, forget to take devices to collect data, limit the simple size because of the number of devices, etc.), and the phenomenon that the smartphone is becoming one of necessities of life, there is a great chance for the smartphone to replace dedicated GPS devices. Although, several general reviews have been done about smartphone-based GPS travel survey in the literature review section in some articles, a systematic review from smartphone-based GPS data collection to travel mode detection has none. The included studies were searched from six databases. The purpose of this review is to critically assess the current literature on the existing methodologies of travel mode detection based on GPS raw data collected by smartphones. Meanwhile, according to the systematic comparison among different methods from data-preprocessing to travel mode detection, this paper could carefully provide the Strengths and Weaknesses of existing methods. Furthermore, it is the crucial step to develop the methodologies and applications of GPS raw data collected by smartphones.

This paper presents an optimized energy management strategy for Li-ion power batteries used on electric vehicles (EVs) at low temperatures. Under low-temperature environments, EVs suffer a sharp driving range loss resulted from the energy and power capability reduction of the battery. Simultaneously, because of Li plating, battery degradation becomes an increasing concern as temperature drops. All these factors could greatly increase the total vehicle operation cost. Prior to battery charging and vehicle operating, preheating battery to a battery-friendly temperature is an approach to promote energy utilization and reduce total cost. Based on the proposed LiFePO4 battery model, the total vehicle operation cost under certain driving cycles is quantified in the present paper. Then given a certain ambient temperature, a target temperature of preheating is optimized under the principle of minimizing total cost. As for the preheating method, a liquid heating system is also implemented on an electric bus. Simulation results show that the preheating process becomes increasingly necessary with a decreasing ambient temperature; however, the preheating demand declines as driving range grows. Vehicle tests verify that the preheating management strategy proposed in this paper is able to save total vehicle operation cost.

This article introduces a novel payload structure, which has been experimentally proven to have smaller impact force while the carried internal electronics remains intact. The study describes in details how materials and geometric structures were chosen based on information analysis. It is clarified how possible geometric structures and materials can be chosen to yield optimal efficiency. Finite element method simulations were carried out to investigate the mechanical properties of several geometric structures, which has led to the dodecahedron form. For the frame, Polylactic Acid were chosen as an optimal material. A low air pressure test for parts of the structure, and also the whole structure were carried out with successful results. Drop tests, with force measuring sensors and high speed videos, were carried out for measuring and comparing the maximal impact force of classical payloads and the novel one. Laboratory and real life tests demonstrated that the developed new structure is safer and it is applicable.

Productivity has been modest in construction due to many reasons, especially project-specific operations and fragmentation. The main aim of this research is to map the challenges towards industrialization in construction through a comparative study of the manufacturing industry. An inductive approach and a qualitative method are followed by applying semi-structured inter-views, and node-based thematic analysis. The key elements of industrialization in mature man-ufacturing companies are benchmarked. The findings indicate a specific order of steps for indus-trialization in construction. Data and information management with achieved systematization have been sources of productivity in manufacturing companies. However, the systematization starts from the offering, construction companies need to define their offering, that is the products, and define their respective data. Only accurate and good quality data on products enables the systematization of order delivery processes, which are the engine for a company’s success or failure. Continuous efficiency improvement is only possible with systematized processes and respective data related to the processes. The originality involves clarifying the industrialization of construction companies via products, respective data, and processes considering industrialized manufacturing companies.

Under the same seismic load, different local topography will have different effects, which is an important research field in seismic engineering. Hills are connected with valleys is a very typical terrain. Taking this terrain as an example, its response to the most destructive SH waves in the earthquake is studied. By simplifying and dividing the model, the wave functions satisfying the wave equation and boundary conditions in each region are constructed by using the complex function and moving coordinate method. The equations satisfying the boundary continuity conditions are established. With the help of calculation software, the numerical results are obtained. The influence of different parameters on ground motion is discussed.

In this paper, we dive into the exciting world of wireless communication, focusing on how millimeter-wave technology and Multiple-Input Multiple-Output phased array antennas are shaping the future of 5G and the upcoming 6G technologies. We cover the latest advancements in millimeter-wave and beam-forming technologies, emphasizing their role in enhancing network security and efficiency in automotive vehicles through dual radar communication. Our discussion spans the benefits, applications, challenges, and solutions of these technologies individually from millimeter-wave to beam-forming technology and joint radar communications, alongside a look at their theoretical and practical implementations. We emphasize the integration of beam-forming technology in joint radar communications for future automotive vehicles and its impact on automotive systems, smart cities, and the Internet of Things (IoT). Looking ahead, we discuss the potential of these technologies to transform future tech landscapes, while also addressing the security implications of merging communication and radar capabilities. This paper aims to provide a clear view of the advancements and prospects of millimeter-wave, beam-forming, and dual radar communication technologies.

The up-to-date challenge towards clean road transport are non-exhaust emissions. Important advances regarding measurement systems, including well defined characterisation techniques, as well as regulation, will happen in the next few years. In this work we present detailed results of particle emissions from a test bed for wheel suspension and brakes, consisting of aerosol (size distribution, particle number (PN) and mass (PM)) and electron microscopy measurements (EM) under different load conditions. Standard tyres and brakes from series production were tested with a high-load driving cycle while particle measurements were conducted by gravimetric measurements and with a TSI SMPS, a TSI APS and a GRIMM OPS. Furthermore, samples were analyzed by electron microscopy. A bimodal particle size distribution (PSD) was obtained with the SMPS, with peaks at 20nm and around 400nm. EM analysis of >1400 single particles from the electrostatic sampler matches the PSD results. EM analysis also showed ultrafine particles, mainly from O, Fe, Si, Ba, Mg and S and also fractal particles with high C fractions. Our results suggest, in agreement with previously published literature, that particulate emissions are related to brake disc temperature and occur in significant amounts above a threshold temperature.

Companies are increasingly focusing on sustainable business practices. Internal and external stakeholders’ expectations manifest in legal requirements, national and international standards, and market and customer expectations, among other things, must be considered. In addition to profit maximization as the usual target for corporate management, management must consider environmental sustainability aspects such as resource efficiency, greenhouse gas intensity, and a company's emissions behavior. In addition, social aspects relating to the company's employees, the immediate urban environment, the situation in the supply chain, and effects on the market environment must increasingly be considered. Specifically, companies are faced with the chal-lenge of dealing with conflicting objectives regarding the various aspects of sustainability and, if necessary, weighing them up against each other. These trade-offs must be made against the company's socio-economic and ecological environment, corporate strategy, and sustainability goals. This paper provides an overview of current approaches and research gaps on this topic through a literature review. It shows a lack of methods and frameworks to specifically deal with trade-offs and conflicts of goals.

Logistics plays an important role in globalized companies and contributes to the development of foreign trade. A large number of external conditions, such as recession and inflation, affect logistics. Therefore, managers should find ways to improve operational performance, enabling them to increase efficiency while considering environmental sustainability due to the industry’s large scale of energy consumption. Based on data collected from the financial reports of top global logistics companies, this study uses a DEA model to calculate corporate efficiency by implementing a Grey forecasting approach to forecast future sustainability values. Consequently, the study addresses the problem of how to enhance operational performance while accounting for the impact of external conditions. This research can help logistics companies develop operation strategies in the future that will enhance their competitiveness vis-à-vis rivals in a time of global economic volatility.

Abstract: Efforts for carbon emission reduction have been identified as a major climate change mitigation target in the Paris Agreement. The 26th Conference of Parties to the United Nations Framework Convention on Climate Change highlighted the worldwide effort for cleaner and greener mining, urging the mineral industry to embrace greener operational emissions reduction technologies and strategies. Ghana pledged at the Paris Conference to reduce CO2 emissions by 15% and increase renewable energy share to 10% of the national energy mix. Here the fundamental question is how Ghana’s mining industry can contribute to CO2 emission reduction efforts. This paper investigates barriers to low-carbon emission policy implementation among mining companies in Ghana. The questionnaire survey was conducted among Ghana’s four large-scale gold mining companies. As the sample number of available companies is limited, we used a descriptive analysis to assess the responses. The results show that the companies expressed widely different ways to respond to the issues of cost, a government policy/regulations for carbon emission reduction, and the adoption/acquisition of low-carbon technologies. Those companies that are relatively less prepared for this endeavor emphasized the uncertainties of securing sufficient energy in case of using low-carbon technologies. They also expressed a need for more trained workers to handle low-carbon technologies. All companies agreed with a expected high cost of adopting low-carbon options. There was a communication gap with the relevant government ministry about low-carbon mining options where the government should be able to facilitate the involvement of othe low technology providers, such as solar PV installation.

In this paper, an adaptive proportional and integral (PI) controller for speed control of electric drives is developed. The adaptive PI controller is designed based on model reference adaptive identification and the Lyapunov function so that the system stability can be proved. To identify the inertia, the viscous friction torque coefficient, and the load torque simultaneously and smoothly, sinusoidal speed reference is usually employed. A modified motion equation considering the low-pass filter for feedback speed and the Coulomb friction torque is introduced and the relationship between the identified parameters and their actual values are clarified. A high-precision digital simulation model is built based on MATLAB/Simulink. The effectiveness of the proposed method is verified by simulations under various conditions.

The world is facing a great technological transformation towards full autonomous vehicles, where optimists predict that by 2030, autonomous vehicles will be sufficiently reliable, affordable and common to displace most human driving. To cope with these trends, reliable perception systems must enable vehicles to hear and see all the surroundings, being light detection and ranging (LiDAR) sensors a key instrument for recreating a 3D visualization of the world in real time. However, perception systems must rely in accurate measurements of the environment. Thus, sensors must be calibrated and benchmarked before being placed on the market or assembled in a car. This article presents an Evaluation and Testing Platform for Automotive LiDAR sensors with the main goal of testing not only commercially available sensors, but also sensor prototypes currently under development in Bosch Automotive Electronics division. The testing system can benchmark any LiDAR sensor under different conditions, recreating the expected driving environment to which such devices are normally subjected. To characterize and validate the sensor under test, the platform evaluates several parameters such as the field of view (FoV), angular resolution, sensor’s range, etc. This project results from a partnership between the University of Minho and Bosch Car Multimedia Portugal, S.A.

The oil and gas industry in Nigeria, a vital contributor to the nation's economy, has long been associated with significant environmental challenges. Pollution, habitat destruction, and greenhouse gas emissions have raised global concerns about sustainability and corporate responsibility. This empirical study explores the relationship between environmental accounting practices and the financial performance of listed oil and gas companies in Nigeria. We investigated eight oil and gas companies that are publicly traded on the Nigerian Stock Exchange Market (NGX) as of January 17, 2022, from 2011 to 2022. The study employs Driscoll-Kraay standard errors and reveals that environmental accounting had significant effects on returns on assets, earnings per share, and liquidity ratio. The study revealed that the implementation of environmental accounting practices had diverse effects on the performance of oil and gas companies in Nigeria. The findings encourage policymakers and stakeholders in the sector to utilise the insights and design more effective regulations and incentives that promote environmental corporate responsibility. Also, valuable insights into the potential benefits and challenges associated with adopting environmental accounting practices, and influencing the decision-making processes of corporate stakeholders were provided to ensure sustainability in terms of improved financial performance of the oil and gas sector in Nigeria.

Sustainability is a characteristic manifested in the ability to maintain the necessary level of performance for construction companies when risk factors arise during the implementation of investment and construction projects. The risk factors that arise during the implementation of in-vestment and construction projects differ in nature, degree of influence, and other characteristics. Ignoring these factors and measures to manage them often leads to critical consequences in the form of disruptions in the timing of work. Risk is a combination of the probability and consequences of the occurrence of adverse events. The article considers the concept of risk as a potential possibility of occurrence of adverse situations and related consequences when exposed to these factors. Risk factors are characterized by surprise, discreteness of changes, the presence of threshold values, upon reaching which a transition to a different mode of operation is required. The article discusses the risk factors arising at the construction stage, their classification. A methodology has been developed that includes conducting a survey in the form of a questionnaire in order to collect information about risk factors that affect the implementation of investment and construction projects. Experts with experience in the construction sector were involved in the survey. The processing of the survey results made it possible to assess the significance of various risk factors in investment and construction projects. Thus, statistical and expert methods were used in the study. The results showed that financial, technical, legal, economic, managerial and natural factors have the greatest impact on investment and construction projects. It is recommended to pay special attention to the listed factors when developing measures aimed at preventing risks and their consequences. The methodology described in the study can be used by construction companies in strategic planning. The analysis of the stability of construction companies, depending on their use of various ways to counteract risk factors, allowed us to develop a number of practical recommendations to reduce the impact of the studied factors on achieving the goals of investment and construction projects.

Additive manufacturing (AM) techniques are widely investigated for the cost-effective use of titanium (Ti) alloys in various aerospace applications. One of the AM techniques developed for such applications is plasma transferred arc solid free-form fabrication (PTA-SFFF). Materials manufactured through AM techniques often exhibit anisotropies in mechanical properties due to the layer-by-layer material build. In this regard, the present study investigates the isothermal directional fatigue of Ti-TiB metal matrix composite (MMC) manufactured by PTA-SFFF. This investigation includes rotating beam fatigue test, electron microscopy, and fatigue calculations. The fatigue experiments were performed at 350 ºC using specimen with the test axis oriented diagonally (45º) and parallel (90º) to the AM builds directions. The fatigue values from the current experiments along with literature data find that Ti MMC manufactured via PTA-SFFF exhibit fatigue anisotropy reporting highest strength in 90º and lowest in perpendicular (0º) AM build directions. Further, the electron microscopy investigations on 0º, 45º, and 90º AM build specimens reveal frequent TiB clusters in all three AM build directions and suggest that the spread of these TiB clusters play a role in fatigue anisotropy. Moreover, the fatigue calculations were performed using both the Paris’ and recently reported modified Paris’ equations. Comparison of R^2 values for these calculations show that modified Paris’ equation predicts the fatigue life of AM Ti-TiB MMC more accurately than the Paris’ equation.

Product Development Process is widely known among industry and automobile companies. With the advance of technology and the need to improve product efficiency, many companies have been applying Lean Thinking principles. Their benefits lead those companies to implement their concepts and tools, like Value Stream Design in Indirect Areas, Obeya, Just-in-time (JIT) which is based on the production control system developed and implemented by Toyota. This article describes the case study of the implementation of Lean Product & Process Development (LPPD) on the current Product Development Process (PDP) in an automotive company. The PDP was created by the organization and adapted from Advanced Product Quality Planning (APQP). The main findings were a Value Stream Design model of an improved PDP as a useful and successfully contribution for the company. These improvements reduced the product development lead time from 700 days to 369 days. The process efficiency increased from 68% to 85%. The communication and transparency between the cross-functional team (CFT) was improved and show promise for achieving a successful launch of new products.

Virtual validation of radar sensor models is becoming increasingly important for the safety validation of adf. Therefore, methods for quantitative comparison of radar measurements in the context of model validation need to be developed. This paper presents a novel methodology for accessing and quantifying validation measurements of radar sensor models. This method uses edf and the so-called dvm to effectively quantify deviations between distributions. By applying this metric, the study measures the consistency, reproducibility and repeatability of radar sensor measurements. Different interfaces and different levels of detail are investigated. By comparing the radar signals from real world experiments where different objects are present, valuable insights are gained into the performance of the sensor. In particular, the research extends to assessing the impact of varying rain intensities on the measurement results, providing a comprehensive understanding of the sensor’s behaviour under these conditions. This holistic approach significantly advances the evaluation of radar sensor capabilities and enables the quantification of the maximum required quality of radar simulation models.

Although traditional automotive development has mainly focused on functional safety, as the number of automotive hacking cases has increased due to the growing Internet connectivity of automotive control systems, security is also becoming more important. Accordingly, various international organizations are preparing cybersecurity regulations or standards to ensure security in automotive development by emphasizing the concept of security-by-design(i.e. security engineering) which emphasizes trustworthiness from the beginning of development. The problem, however, is that no specific methodology has been suggested. In this paper, we propose a specific security-by-design methodology for automotive development based on Secure System Development Life Cycle (secure SDLC) standards and evidence-based standards. Our methodology could be easily used in the actual field as it is more general and detailed than existing secure SDLC standards and research. Also, since it satisfies all requirements of United Nations Economic Commission for Europe (UNECE) regulation, automobile manufacturers could respond to the upcoming cybersecurity regulation with our methodology.

Vehicle safety promises to be one of the Advanced Driver Assistance System (ADAS) biggest benefits. Higher levels of automation remove the human driver from the chain of events that can lead to a crash. Sensors play an influential role in vehicle driving as well as in ADAS by helping the driver to watch the vehicle’s surroundings for safe driving. Thus, the driving load is drastically reduced from steering as well as accelerating and braking for long-term driving. The baseline for the development of future intelligent vehicles relies even more on the fusion of data from surrounding sensors such as Camera, Lidar and Radar. These sensors not only need to perceive in clear weather but also need to detect accurately adverse weather and illumination conditions. Otherwise, a small error could have an incalculable impact on ADAS. As most of the current study is based on indoor or static testing. In order to solve this problem, this paper designs a series of dynamic test cases with the help of outdoor rain and intelligent lightning simulation facilities to make the sensor application scenarios more realistic. As a result, the effect of rainfall and illumination on sensor perception performance is investigated. As speculated, the performance of all automotive sensors is degraded by adverse environmental factors, but their behaviour is not identical. Future work on sensor model development and sensor information fusion should therefore take this into account.

During the European unification process, they stated the need for drawing up a common energy strategic plan that will affects electricity production system in terms of infrastructure, production and generation. The EU strategic action plans included; reduction in emissions, an increase in renewable energies, energy efficiency. In this light therefore the energy efficiency was booked for researching. This article presents an in-depth study of the challenges in transforming a functioning PMO model to an EPMO model within four electricity companies from different countries within the EU and how those challenges can be address within companies implementing same methodology to bring about electricity production efficiency. Will these identified challenges make it impossible for the companies to achieve electricity production efficiency in the transformation from PMO to EPMO? PMO has been the major methodology used by these companies. To achieve production efficiency, the need for a heavyweight methodology was identified (EPMO) and implemented in four mega electricity producing companies with cross boarder distributions, one from France; Germany; Spain and UK

The increasing complexity of vehicular traffic and the prevalence of accidents, particularly rear-end collisions, necessitate enhancements in automotive safety technologies. Adilights, an innovative automotive lighting system, addresses this need by introducing a dynamic visual communication method between vehicles. This system features a novel design that employs variable-intensity brake lights configured in an upside-down "U" shape to indicate braking severity. The intensity and pattern of the lights change in response to the pressure applied to the brake pedal, providing clear and immediate feedback to following drivers. This design not only improves the perceptibility of braking signals, particularly in dense traffic and poor visibility conditions but also aims to reduce the frequency of rear-end collisions significantly. The paper details the development and testing of Adilights, discusses its integration with current vehicular systems, and evaluates its effectiveness through simulated scenarios. The introduction of Adilights marks a step forward in the use of adaptive lighting systems for enhanced vehicular communication and road safety.\cite{Lee2007RearEnd}

The automotive industry is continuously seeking innovative solutions to improve the energy efficiency and sustainability of vehicles. Among the various energy-consuming systems in automobiles, air conditioning plays a crucial role. However, conventional vapour compression-based air conditioning systems are known for their high energy consumption and environmental impact. In recent years, adsorption technology has gained significant attention as a promising alternative due to its potential for higher energy efficiency and reduced greenhouse gas emissions. This review paper presents a comprehensive analysis of advancements in adsorption air conditioning technology specifically designed for automotive applications. The paper examines the recent research and development efforts in enhancing the performance and practicality of these systems, encompassing areas such as advanced materials selection, and system integration strategies. Furthermore, this review highlights the benefits and challenges associated with implementing adsorption air conditioning systems in vehicles. The environmental impact and potential for waste heat recovery are also discussed. Additionally, emerging trends, such as hybridization with conventional vapour compression systems, are explored to further optimize the energy efficiency and sustainability of automotive air conditioning. By critically evaluating the existing literature and research advancements, this review provides insights into the state-of-the-art thermally driven technologies for automotive applications.

With the emergence of autonomous functions in road vehicles, there has been an increased use of Advanced Driver Assistance Systems comprising various sensors to perform automated tasks. Light Detection and Ranging (LiDAR) is one of the most important types of optical sensor that detects the positions of obstacles, representing them as clusters of points in 3-dimensional space. LiDAR performance degrades significantly when driving in rain as raindrops adhere to the outer surface of the sensor assembly. The performance degradation behaviors include missing points and reduced reflectivity of the points. It was found that the extent of degradations is highly dependent on the interface material properties, which subsequently affects the shapes of the adherent droplets, causing different perturbations to the optical rays. A fundamental investigation is performed on the protective polycarbonate cover of the LiDAR assembly coated with four classes of materials – hydrophilic, almost-hydrophobic, hydrophobic, and superhydrophobic. Water droplets are controllably dispensed onto the cover to quantify the signal alteration due to each droplet of various sizes and shapes. To further understand the effects of droplet motion on LiDAR signals, sliding droplet conditions are simulated using numerical analysis and validated with physical optical tests using a 905 nm laser source and receiver to mimic the LiDAR detection mechanism. Comprehensive explanations are presented on LiDAR performance degradation in rain from both material and optical perspectives. These can aid component selection and the development of signal enhancing strategies for integrating LiDARs in vehicle designs to minimize the impact of rain.

The procedures used to create modern cars require extensive thought in various relevant scientific domains. Arguably, the most challenging obstacle facing the automobile sector is managing production facilities by integrating software production lines and CI/CD. All this is determined by market demands, the engine of a vehicle, and the complexity of assembling the entire car and installing its corresponding embedded software. As a result, concerns about various types of global change have grown, as well as the lack of the ability to use fossil fuels, creating a substantial impact on the purchase and sale of modern automobiles. The research foundation is reflected in covering strategies for the deployment and administration of software, as well as opportunities for business improvement in particular production processes. This article strives to provide a summary of a scientific investigation of original equipment manufacturers, market segmentation, and the effects of global market changes on automotive manufacturing by examining the correlation between certain changes in the purchase of a specific brand and the powertrain of a vehicle. The research tries to examine numerous datasets from the United States of America and Washington State, on the basis of which we may estimate possible future changes in the automotive industry’s sales.

Virtual reality (VR) can play a key role in automotive marketing research, lowering costs and shortening the time it takes to bring a new product to market. However, there are still few VR applications that support automotive customers' experiences during the early stages of product development. Through a systematic review of literature and patents, this study aims to identify the challenges and opportunities for the application of virtual reality in car clinics, and to categorize them into attributes. We searched through the knowledge databases of PatentScout, ScienceDirect, Springer, and IEEEXplore. We found 72 patents with a high concentration in a few inventors. The United States of America presented the greatest number of records and the most common applications related to the apparatus for automatically reading respondents' reactions in a virtual environment. In terms of articles, we found 19 research papers that discussed sixteen categories identified as challenges and opportunities for automotive marketing research: 1) cost, 2) location to customers, 3) flexibility in interactions, 4) model transportation, 5) depth perception, 6) haptic perception, 7) motion, 8) movement perception/ physical collision, 9) color and texture, 10) sound feedback, 11) product interaction/manipulation, 12) visual-spatial, 13) graphic quality, 14) intuitiveness, 15) cybersecurity and 16) cybersickness. We conclude that the automotive industry can employ virtual reality for marketing research, but relevant elements such as hardware and software definition, stimulus quality, and research objectives, among others, must be considered.

This paper presents the microstructural and mechanical properties of low and medium carbon advanced high-strength forging steels developed based on the third generation advanced high-strength sheet steels, in conjunction with those of conventional high-strength forging steels. Hot-forging followed by an isothermal transformation process considerably improved the mechanical properties of the forging steels. The improvement mechanisms of the mechanical properties were summarized by relating to the matrix structure, the strain-induced transformation of metastable retained austenite and/or a mixture of martensite and austenite.

The purpose is to verify trends of scientific production from 2010 to 2020, considering the best universities of the United States, China, the European Union (EU) and private companies. The top 30 universities in 2020 in China, the EU, and the US and private companies were selected from the SCImago institutions ranking (SIR). The positions in 2020, 2015, 2010 in SIR and three sub-indicators were analyzed by means of non-parametric statistics, taking into consideration the effect of time and group on rankings. American and European Union universities have lost positions to Chinese universities and even more to private companies, which have improved. In 2020, private companies have surpassed all other groups considering Innovation as sub-indicator. The loss of leadership of European and partly American universities mainly concerns research linked to the production of patents. This can lead to future risks of monopoly that may elude public control and cause a possible loss of importance of research not linked to innovation.

This paper exposes the initial part of a larger research on the impact of the automotive on human health and the quality of life and environment. After a brief introduction on the need for responsible and sustainable approaches and few questions on the subject, some considerations and statistical data are presented, based on a study of the literature on the impact of road traffic and vehicles noise and vibration on people's comfort and health and their quality of life. The research results show, based on official statistics, the significant harmful impact of noise and vibration from motor vehicles and road transport on people's health and quality of life, especially in urban areas during the day. Also, the significant increase in the number of electric and hybrid vehicles from one year to another, a reality and a necessity nowadays, and the awareness that electric vehicles are not perfectly quiet and comfortable, open new research opportunities and require the development of new standards, materials, tools, equipment and test methods in the field of NVH, in a sustained synergistic approach from all stakeholders, to meet the needs and demands of today's consumers, and to comply with existing regulations and standards on environmental protection and sustainable development.

The violation of data integrity in automotive Cyber-Physical Systems (CPS) may lead to dangerous situations for drivers and pedestrians in terms of safety. In particular, cyber-attacks on the sensor could easily degrade data accuracy and consistency over any other attack, we investigate attack detection and identification based on a deep learning technology on wheel speed sensors of automotive CPS. For faster recovery of a physical system with detection of the cyber-attacks, estimation of a specific value is conducted to substitute false data. To the best of our knowledge, there has not been a case of joining sensor attack detection and vehicle speed estimation in existing literatures. In this work, we design a novel method to combine attack detection and identification, vehicle speed estimation of wheel speed sensors to improve the safety of CPS even under the attacks. First, we define states of the sensors based on the cases of attacks that can occur in the sensors. Second, Recurrent Neural Network (RNN) is applied to detect and identify wheel speed sensor attacks. Third, in order to estimate the vehicle speeds accurately, we employ Weighted Average (WA), as one of the fusion algorithms, in order to assign a different weight to each sensor. Since environment uncertainty while driving has an impact on different characteristics of vehicles and cause performance degradation, the recovery mechanism needs the ability adaptive to changing environments. Therefore, we estimate the vehicle speeds after assigning a different weight to each sensor depending on driving situations classified by analyzing driving data. Experiments including training, validation, and test are carried out with actual measurements obtained while driving on the real road. In case of the fault detection and identification, classification accuracy is evaluated. Mean Squared Error (MSE) is calculated to verify that the speed is estimated accurately. The classification accuracy about test additive attack data is 99.4978%. MSE of our proposed speed estimation algorithm is 1.7786. It is about 0.2 lower than MSEs of other algorithms. We demonstrate that our system maintains data integrity well and is safe relatively in comparison with systems which apply other algorithms.

Digital transformation of companies is often referred to as a future track and a strategic path towards ensuring the survival and sustainability of companies. In this paper, we aim to outline this transformation process in Tunisian companies and identify its driving factors and finally explain its key success factors. To this end, we examine a sample of 70 companies operating in all economic sectors. The results indicate that such a digital strategy has a significant and a positive effect on the success of digital transformation of companies. Leadership has an effect at a low level of digital maturity. On the other hand, corporate culture does not have a significant effect on digital transformation. These results contribute to explaining this emerging phenomenon by focusing on the driving factors as well as the factors that contribute to its success.

This study tries to focusing on applying information communication technology for economic importance of Mid Oil Company (MDOC), which is among contemporary oil companies in Iraq. Since ICT forms a significant aspect of achieving organizational economic objectives, most of public and private bodies seek to utilize ICT tool and techniques to improve work efficiencies. The emerging growth in ICT has made it process and service automation possible in managing organizational activities. To determine this effect of ICT on organizations, this study formulated statistical research model at MDOC through using fifteen questionnaires, which were distributed on three axes. The outcome of the questionnaire analysis revealed that there is inadequate comprehensive infrastructure to suitably support ICT within the selected organization management. In addition, it revealed that there are no ideal standards to maintain and sustain internet networks. Based on these revelations, the study presents recommendation for the adoption of ICT with the aim of minimizing cost, enhancing communication and managing infrastructure. Also recommends the need to support IT department within an organization, with essential equipment, in terms of man and machine, for better efficiency to employ the key of ICT Impact in Iraqi governmental oil companies.

This article presents a review of resources for batteries with a specific focus on sustainability aspects related to raw materials, electrode and electrolyte chemistries suitable for the automobile industry. We emphasize the importance of prioritizing sustainability in battery technology evolution, which is expected to shift towards earth-abundant materials. One notable advancement in this direction is the utilization of glass solid-state electrolytes, known for their high ionic conductivity, low electronic conductivity, and high dielectric constant. However, our review suggests that further research should explore synthesis methods to modify anisotropic properties, enhancing the performance of solid-state electrolytes, particularly in facilitating the flow of ions.

Artificial Intelligence (AI) is an automation mechanism that runs in a computer system performing tasks that normally require human intelligence, such as visual perception, speech recognition, decision making or translation [1]. Some authors argue that recent developments in AI are leading to a wave of innovation in organizational design and changes to institutionalized norms of the workplace [2]. Techno-optimists even named this present phase the ‘second machine age’, arguing that it now involves the substitution of the human brain (Brynjolfsson and McAfee 2014). Potentially, the ability to apply AI in a generalized way can produce significant technical, economic and social effects in firms. But how many of these AI applications are ready and how far can they be from reaching the manufacturing industry market? The paper will answer the question: what are the implications on industrial productivity and employment in the automotive sector with the recent automation trends in Portugal? We will focus on AI as the most relevant emergent technology to understand the development of automation in areas related to robotics, software, and data communications in Europe (Moniz 2018). R&D investments in industrial processes in general may reflect productivity improvements derived from the increased automation process. Our results will be based on case studies from the automotive and components sector combined with database search by keywords that signal intelligence automation developments and AI applications selected from national R&D projects (on robotics, machine learning, collaborative tools, human-machine interaction, autonomous systems, etc) supported by European structural funds. The implications on industrial productivity and employment will be discussed in relation to automation trends in the automotive sector.

The aim of this work was to investigate the microstructure and the mechanical properties of la-ser-welded joints combined of DP800 and DP1000 high strength thin steel sheets. The welded joints (WJ) comprised of similar/dissimilar steels with similar/dissimilar thickness were consisted of different zones and exhibited similar microstructural characteristics. The trend of microhard-ness for all WJs was consistent, characterized of the highest value at hardening zone (HZ) and lowest at softening zone (SZ). The degree of softening was more severe and the size of SZ was wider in the WJ combinations of DP1000 than DP800. The tensile test fractures were located at the base material (BM) for all DP800 weldments, while the fractures occurred at the fusion zone (FZ) for the weldments with DP1000 and those with dissimilar sheet thicknesses. The DP800-DP1000 weldment presented similar yield strength (YS) and ultimate tensile strength (UTS) values but lower elongation (EI) in comparison with the DP800-DP800 weldment, which showed similar strength properties as the BM of DP800. However, the EI of DP1000-DP1000 weldment was much lower in comparison with the BM of DP1000. The DP800-DP1000 weldment with dissimilar thicknesses showed the highest YS and UTS values compared with the other weldments, but with the lowest EI. The fatigue fractures occurred at the WJ for all types of weldments. The DP800-DP800 weldment had the highest fatigue limit and DP800-DP1000 with dissimilar thick-nesses had the lowest fatigue limit. The fatigue crack initiated from the weld surface.

The Thailand automotive industry grapples with complex challenges in service parts management, demanding a strategic approach for post-sales operations. This research unveils a tailored methodology, leveraging historical sales data, refined part classifications, and strategic decision rules. A high-level overview of the automotive supply chain emphasizes interconnected stakeholders. The systematic methodology delves into part categorization, decision rules, and data analysis. Decision rule outcomes, exceptions, and contingency solutions showcase efficacy. A cost impact assessment highlights substantial savings. Visualization tools offer nuanced perspectives. Optimized service parts classification, robust stocking decision rules, and cost-effective strategies emerge. Support Vector Regression excels in forecasting, with recommendations for dynamic stocking. Implications extend to the broader industry, offering efficiency and service quality blueprints. Acknowledging limitations and suggesting future research, this study contributes a valuable framework for Thai automotive service parts management.

Surface defect detection is a crucial step in the process of automotive wheel production. However, the task possesses challenges due to complex background and a wide range of defect types. In order to detect the defects on the wheel surface accurately and quickly, this paper proposes a YOLOv5-based algorithm for automotive wheel surface defect detection. The algorithm trains and tests the YOLOv5s model using the self-created automotive wheel surface defect dataset, which contains four kinds of defects: linear, dotted, sludge, pinhole. The extensive experimental results demonstrate that the deep learning network trained by our method can achieve an average accuracy of 71.7% and 57.14 FPS. Our findings prove that this detection algorithm performs better than other common target detection algorithms and meets the real-time requirements of industrial applications.

Pakistan is under developing country and it has an unpredictable market nature of shareholder-investors observe the company’s performance. This research could help to companies in understanding financial behavior, attitude and investors’ satisfaction in stock trade. Financial behavior is comparatively new subject in Pakistan therefore; this study has examined the financial behavior and attitude of investors. The behavioral finance that has been attempted to understand the positive experiences influences investors’ financial behavior. This study has find out that investor satisfaction is strongest in influence of positive financial behavior of investor and trader in stock trading; positive experience and brokers suggestions are strengthens the investment decision of investors and increases behavior loyalty to prefer over competitor. The main purpose of research to determine the effect of financial behavior on investors’ attitude and behavioral loyalty and investors’ satisfaction to preference over competitor. The research framework links with experiences in stock trade for positive (negative) experiences, attitude and financial behavior is developed. The research framework is measured data from sample of Karachi and Karachi Stock Exchange; the data is analyzed in smart PLS based on PLS-SEM. This study focused on trading experience with company’s active investors and traders in banking industry in Pakistan. The future research could be research in other sectors with inter-related issue of investors and traders (brokers) in stock trade. This is the first study in this research area; this study will be determine the experiences with positive (negative) financial behavior, attitude, satisfaction and behavioral loyalty of investors and traders in stock trade. Therefore, adding in this area of study which will help understanding the investors and traders attitude, preference and financial behavior in financial market.

Nutraceuticals are combination of nutrients and pharmaceuticals and these are derived from various plants, microbes and animals too. The food products that are considered as nutraceuticals are categorised based on the availability in the market. It is a medical approach to improve health and remedy for illness. Nowadays there is an increase in shift towards use of nutraceuticals as its usage provides preventive therapies to various chronic diseases. Various natural nutraceuticals are based on extracts from Ginger, turmeric, garlic, amla, cinnamon, aloe vera etc. A wide variety of therapeutic values are provided by them such as anti-inflammatory, antibacterial, antifungal properties, allergy relief, antidiabetic and cardiovascular problems. India is in its infancy stage but have many emerging companies that are trying to meet the demand of growing population. Overall ‘Nutraceuticals’ has been known as a new era of well being, in which the food industry has become a main player.

Considering the manufacturing of automotive components, there exists a dilemma around the substitution of traditional Cast Iron (CI) with lighter metals. Nowadays, aluminium alloys, being lighter compared to traditional materials, are considered as a more environmentally friendly solution. However, the energy required for the extraction of the primary materials and manufacturing of components is usually not taken into account in this debate. In this study, an extensive literature review has been performed to estimate the overall energy required for the manufacturing of an engine cylinder block using (a) cast iron and (b) aluminium alloys. Moreover, data from over 100 automotive companies, ranging from mining companies to consultancy firms, have been collected in order to support the soundness of this investigation. The environmental impact of the manufacturing of engine blocks made of these materials is presented with respect to the energy burden; the “cradle-to-grave approach” has been implemented to take into account the energy input of each stage of the component lifecycle starting from the resource extraction and reaching to the end-of-life processing stage. Our results indicate that although aluminium components contribute towards reduced fuel consumption during their use phase, the vehicle distance needed to be covered in order to compensate for the up-front energy consumption related to the primary material production and manufacturing phases is very high. Thus, the substitution of traditional materials with lightweight ones in the automotive industry should be very thoughtfully evaluated.

In response to the growing need for efficient energy conversion technologies, this pa-per introduces an innovative Tubular Thermoelectric Generator (TTEG), specifically de-signed for high-efficiency conversion of waste heat into electrical energy. Unlike conven-tional flat plate thermoelectric generators (FTEGs), the TTEG incorporates full-ring ther-moelectric elements within a tubular layout, offering a novel approach to thermal energy recovery from fluid-based systems. This design significantly enhances the heat transfer capabilities, thereby improving the efficiency of energy conversion. Comprehensive simulations and analyses form the core of this study, where the per-formance of the TTEG is rigorously compared with traditional FTEGs. These comparisons highlight the advantages of the tubular design in terms of energy conversion efficiency and practical applicability in various scenarios. The findings reveal that the TTEG not only outperforms its flat plate counterparts but also presents a scalable and adaptable so-lution for waste heat recovery in a wide range of industrial and automotive applications. This research contributes to the field of energy science and technology by presenting a detailed experimental setup, complete with reproducible procedures and results. It opens new pathways for the development of more sustainable and efficient energy conversion systems, aligning with the goal of harnessing renewable and sustainable energy sources. The potential applications of this technology in enhancing energy efficiency and reducing environmental impact are vast, making it a significant step forward in the quest for clean and sustainable energy solutions.

Greenhouse gas (GHG) emissions from human activities have climbed significantly above pre-pandemic levels and reached record highs that unequivocally accelerate global warming. Industry has a significant impact on climate change, emitting at least 21 % of global GHGs and making little overall progress toward its reduction until now. Reducing industry’s emissions requires coordinated action along the value chains in order to promote mitigation options, such as energy and material efficiency, circular material flows, and transformative changes within production processes. The authors analyzed the GHG emissions generated during the manufacturing of three different products of automotive suppliers located in Austria. Despite previous efforts toward an environmentally compatible fabrication, additional and significant reduction potentials were identified. These measures for product carbon footprint (PCF) reduction included the sourcing of low-carbon materials (which are already available on the market), more extensive use of renewable energy, and changes towards more resource efficient manufacturing processes and machinery. Depending on the materials used, the PCF can be reduced by up to 80 %. The findings serve to prepare for future PCF reporting regulations and illustrate reduction potentials to achieve future market advantages, especially when PCFs become an awarding criterion.

5G low-earth orbit satellite communications offer enhanced wireless coverage beyond the reach of 5G terrestrial networks, with important implications, particularly for automated and connected vehicles. Such wireless automotive mass-market applications demand well-designed compact user equipment antenna terminals offering non-terrestrial jointly with terrestrial communications. The antenna should be low-profile, conformal, and meet specific parameter values for gain and operational frequency bandwidth, tailored to the intended applications, in line with the aesthetic design requirements of passenger cars. This work presents an original concept for a dual-band nested circularly polarized automotive user terminal that operates at the S-band frequencies around 3.5 GHz and Ka-band frequencies around 28 GHz, namely within the 5G new-radio bands n78 and n257, respectively. The proposed terminal is designed to be integrated into the plastic components of a passenger vehicle. The arrays consist of 2×2 aperture-coupled corner-truncated microstrip slot patch antenna elements for the n78 band and of 4×4 single-layer edge-truncated microstrip circular slot patch antenna elements for the n257 band. The embedded arrays offer, across the two bands, respectively 9.9 and 13.7 dBi measured realized gain and 3-dB axial ratio bandwidths of 100 and 1500 MHz for the n78 and n257 bands along the broadside direction. Detailed link budget calculations anticipate uplink data rates of 21 and 6 Mbit/s, respectively, deeming it suitable for various automotive mobility and internet-of-things applications.

A friction loss model for brake testing platform is constructed to revise the braking force test results, which can largely improve the accuracy of automotive brake performance testing. Specifically, the influence of tire pressure, vehicle axle load, placement angle and vehicle speed on the friction loss is tested and analyzed on a wheelbase adjustable automotive anti-force brake testing platform. The friction loss model for the platform is constructed based on the defined relative slip and placement angle, which is validated through actual tests on four types of vehicles. The results showed that the maximum relative error between the values of the model calculated simulation and the measured was 2.2%, indicating the friction loss model is valid and can provide a basis for revising the braking force of automotive brake. Meanwhile, the maximum braking force increases from 3982 N to 4772 N, increased by 19.8%, when the placement angle increased from 36.9° to 47.0°. Accordingly, in order to improve the accuracy of detection results of the automotive anti-force rolling brake testing platform, the friction loss caused by the change in the placement angle should be revised, and then braking rate of the vehicle should be judged according to GB 7258-2017 and GB 38900-2020.

Logistics Engineering has transcended over the decades into an approach for competitive benefits in organisational performance and logistics efficiency. Most industries are recognising that significant savings are available to companies that are able to ordinate and improve within their logistics operations. Companies today face great challenges because the successful supply of many products and services needs to the effective integration of logistics activities across a prolongation supply chain and an increasing geographical separation. Moreover, logistics integration approach involves both internal integration for an ordinated, unified process as well as relationships to react flexibly, changeability, and responsibility to customer's demands. In this study, by using of Fuzzy Vikor (F-Vikor), the best combination of RIR was selected and RIR Locating was done. The main aim of this paper is survey and design of the integrated operational logistics network (IOLN) and also, a proposed IOLN to integration of the Iran Khodro Co Supply Network.

In western societies about one in six employees works in shifts. Shiftwork is associated with a number of poor somatic and psychological health outcomes, especially sleep issues. Higher rates of absenteeism and accidents in the workplace are possible consequences. Still, prevention programs and treatment options that are specifically tailored to shift workers’ needs are rare. We devised a 4-week online sleep intervention (n = 21) and compared treatment outcomes to our outpatient treatment for shift workers (n = 12). Measures included the WHO-5, ISI, and ESS scales as well as sleep diaries. Shift workers reported worse symptoms of insomnia than other participants. Results show significant average increases in sleep efficiency (+ 7%) and total sleep time (+ 25 min.), as well as significant improvements regarding insomnia symptoms and wellbeing in the online sample. Rates of improvement did not differ between the online and outpatient samples. Sleep disorders affect a relevant part of the working population, especially shift workers. Online approaches to treatment of these issues seem feasible and effective. Randomized controlled trials are needed.

Insurers act as institutional investors and underwriters of risk, therefore improving their own environmental, social, and governance (ESG) performance is important for the transmission of ESG values to all other economic sectors. We analyze ESG scores of worldwide Property and Casualty (P&C) insurers during 2012-2022, and show that more sustainable insurers have high operating leverage, although their combined ratios and z-scores reveal that they are financially stable. Additional results for the US subsample illustrate that stocks issued by sustainable insurers deliver positive excess returns. Overall, these findings suggest that sustainable practices are associated with the ability of insurers to execute business and create value. This is important for insurance managers, investors, and policy makers, as insurers play a prominent role in promoting economic growth and stability.

Already more than 140 countries consider or have pledged to reach net-zero emission targets by 2050 or earlier and the share of global emissions falling into an emission pricing scheme has steeply increased over the past three years. Even where there are no direct implications for industry (yet), there is a series of subtle pressure points driving an increasing number of companies across the globe to work towards climate neutrality and pledging ambitious emission reduction goals. This article sheds light on the pressure points, the subtle triggers, the underlying considerations as well as the hoped-for benefits for industrial companies from achieving net-zero emissions. The observations and ideas presented in this paper are derived from quantitative data obtained via the Energy Efficiency Index of German Industry (EEI) and qualitative data. Not only societal, work force, supply chain and investor expectations play a large role, but also many strategic considerations which have the potential to make the company more resilient and profitable, particularly in time of crisis. Those companies that do not move towards decarbonisation, on the other hand, may face a costly late-mover disadvantage. This piece uncovers subtle interconnections, helping stakeholders from industry and beyond to grasp opportunities and challenges ahead.

Although the fusion energy sector is at a nascent stage, the private fusion energy market has grown. There are currently 38 private fusion energy companies around the world aiming to commercialise fusion energy in early 2030s and 2040s. Given the capability of fusion energy in transforming today’s energy paradigm and the global character of the market, it is important to analyse how these companies are interacting with international human rights standards. Therefore, this work investigates the involvement of the private fusion energy sector with two voluntary international initiatives in particular: the UN Global Compact and the UN Guiding Principles on Business and Human Rights (UNGP). This study attempts to answer two research questions: (i) Are private fusion energy companies participating in the UN Global Compact? (ii) How are private fusion energy companies publicly implementing the UNGP? Content analysis of secondary data collected from the UN Global Compact, Fusion Industry Association, ITER and companies’ official website as well as published reports is adopted. In summary, this work finds that private fusion energy companies are neither participants nor signatories of the UN Global Compact. Their observance of the UNGP is also very poor. This study contributes to the field by highlighting this gap which the private fusion energy companies need to consider and take measures in order to create a salutary human rights sector.

This contribution addresses dry sliding friction of a “Non-Asbestos Organic” friction material (pad) rubbed against a pearlitic grey cast iron disc. This configuration is commonly used in brakes in US, Europe and Asia. The initial stage of friction is of particular interest when addressing “creep-groan” phenomena occurring in passenger and sport utility vehicles with automatic transmissions. The custom built Universal Friction Tester allowing the variation of sliding speed, test temperature, normal load, stiffness and humidity of the system was used in this experiment in combination with surface analysis by polarized light microscopy, scanning electron microscopy and stylus profilometry. The obtained results indicate that the “stick” phase in the so-called “stick-slip” phenomenon does not really exist. The surfaces of pad and disc are in continuous relative movement. The complexity of surfaces does not allow for a definitive description of exact mechanisms responsible for the detected changes of friction forces. The observed friction process can be rather described as a stretching with possible localized relaxations causing the jerky behavior in the stretching phase, followed by slip between two materials in contact. Understanding of factors contributing to the stretching at different scale levels of friction system is necessary for development of proper models. An accurate friction model should also incorporate the vibrational element introduced by phenomena occurring at the friction surfaces. The absence of heterogeneous regions on the friction surface and “evenly distributed friction level” can help when mitigating creep-groan in the investigated brake system. Understanding of factors on different scales of friction is also required when developing the improved brakes.

With advances in information technology, big data, mobile communications, and robotics, digital technologies are increasingly being used in factories around the world. This digital transformation is named industry 4.0. Today, industrial companies are looking at how to adopt this era and implement these technologies 4.0 while improving their performance and generating more profits. The objective of this paper is to help companies to better choose the appropriate digital technologies according to their activities using a multi-experts-multi-criteria decision-making approach under hesitant fuzzy information. The proposed model is a generic model based on Multi-Agent Systems allowing to have an idea of the parameters necessary to apply the adopted approach. The adopted approach allows a better representation of uncertainty and subjectivity of experts’ judgments. It would be of great interest, especially, when exact quantitative data are not available. A real case company example is exposed (automotive company) towards putting into practice the proposed approach.

Clarifying the impact mechanism of digital transformation of enterprises on the M&A efficiency of listed companies can provide a factual basis for improving capital market regulatory policies. Taking the mergers and acquisitions of listed companies from 2007 to 2021 as a research sample, the influence mechanism of the digital transformation degree of companies on their M&A efficiency was studied. The research results show that the digital transformation of listed companies will improve their M&A efficiency. Digital transformation will reduce the degree of mispricing of stocks of M&A companies, curb conflicts between managers and agents of M&A companies, and improve their M&A efficiency. Further research finds that the promotion effect of digital transformation on M&A efficiency is more significant in non-state-owned companies, with a higher degree of financing constraint and high analyst attention. In the future, regulatory authorities should actively promote the digital transformation of listed companies, curb mispricing and management agency problems in the capital market with digital governance, and improve the efficiency of mergers and acquisitions in the capital market.

Thermal analysis of a hypereutectic Al-Si alloy used for an automotive part was carried out in this research work. Solidification characteristics are recognized from the Temperature-time curve and its corresponding derivatives. This analysis was successfully used in a simulation software program with the aim of improving the resultant simulation accuracy. In this study, different types of molds, with and without cooling systems, were designed and used. The melt present in the furnaces of the factory was used to simulate the casting process. The effect of different cooling rates (1.2ºC/s, 2ºC/s, 2.3ºC/s and 2.9ºC/s) on the solidification parameters have been investigated. Differences in the resultant microstructure between wall and center of the molds have been analyzed and have been related to the T-t curve. Finally, the experimental results clearly indicate that the water-cooling rate of the molds and the melt temperature directly affects the solidification process as well as the final microstructure.

Higher traffic density in Russian cities and less uniform traffic due to congestions are reasons for increased emissions of pollutants contained in exhaust gases of vehicles. The paper presents the modeling results of pollutant dispersion in Magnitogorsk. The analysis of these results shows that now many blocks of flats and social infrastructure of the city are in a zone with an excess of maximum allowable concentration of pollutants. Having summarized the methodological framework formulated by Russian and foreign researchers, the authors systemized the existing methods used to decrease pollutants produced by vehicles. It is proposed to choose an optimal combination of such methods applying a developed mathematical model. By adopting an optimal combination of the methods, it is possible to ensure minimum air pollutant emissions from vehicles, allocating limited financial resources. The mathematical modeling of the solutions on changing traffic density and structure and implementing methods used to decrease pollutants on one of the Magnitogorsk crossroads with the heaviest traffic is used to draw a conclusion about efficiency of the designed model used as a tool for strategic planning of development and transformation of street networks.

This study reports on empirical findings of participatory design workshops for the development of a supportive user experience design system in the automotive. Identifying and addressing this area with traditional research methods is problematic due to the different UX design perspectives that might be conflicting and the related automotive domain limitations. To help resolve this problem, we conducted research with 12 User Experience (UX) designers through individual participatory prototyping activities to gain insights on their explicit, observable, tacit and latent needs. These activities allowed us to explore their motivation to use different technologies; the system's architecture; detailed features of interactivity and describe user needs including Efficiency, Effectiveness, Engagement, Naturalness, Ease of Use, Information retrieval, Self-Image awareness, Politeness, and Flexibility. Our analysis led us to design implications that translate participants' needs into UX design goals, informing practitioners on how to develop relevant systems further.

Habitual entrepreneurs became an important group of entrepreneurs who make a large contribution to the process of wealth creation. Previous studies have indicated that habitual entrepreneurship is a widespread phenomenon. It highlights the need to focus on the habitual entrepreneurs to understand the dynamic aspect of entrepreneurship. The aim of the article is to present the results of preliminary research on the relationships of entrepreneurial behavior of novice entrepreneurs and habitual entrepreneurs, in particular their motivation and impact on the entrepreneurial process. Research were conducted on a sample of 373 small innovative enterprises in the fourth quarter of 2017. The scale of habitual entrepreneurs in the examined sample is 32.44% and is comparable with research carried out in other countries. Survey results reveal that habitual entrepreneurs have greater tendency to create opportunities (introduction new products or services) than novice entrepreneurs. Habitual entrepreneurs also have higher development rate (increase of turnover) and larger share in the international market than novice entrepreneurs. The article also contains indications for further research into the phenomenon of multiple entrepreneurship.

In the paper, a study of the performance of unmanned ground vehicle (UGV), establishes numerical simulation model of the chassis system by three-dimensional software and finite element analysis software. Based on the numerical modelling and analysis, the work focuses on study of the strength and stiffness of the vehicle's chassis and researched the distribution of stress and deformation under the extremal condition. The paper also presents an autopilot design with new cascade control system for an autonomous motion of an unmanned ground vehicle based on Proportional-Integral-Derivative (PID) and Feed-Forward (FF) control. The PID-FF controller is a part of dedicated for presented UGV used in a hybrid control system for precise control and stabilization, necessary to increase the vehicle motion stability and maneuvers precision. The hybrid PID-FF control system proposed for the ground vehicle model gives a satisfactory quality of control, while maintaining the simplicity of the control system. Presented tests performed in area of mechanical design and control analysis gives good results and proves usefulness of designed unmanned device.

This paper investigates the possible failure modes of the product development process in production companies that are active in the B2C markets with a focus on household products. Since these cases require short lead times and are difficult to differentiate, in many instances the end result will not be the desired one and could affect profitability for a season or for good. A model of these possibilities is created and an approach to plan contingencies for their solutioning is proposed in the article. The main guideline is to switch from failure probability determination to accepting failure as inevitable and using digital solutions to reinforce the development process in order to offset its impact. For this goal, an Industry 5.0 Abatement Factor (abbreviated IFAF) is introduced in the contingency planning approach, that factors in the evaluation the low cost of digital instruments and the proper mix of Technology, Humans and AI (abbreviated THAI). The new working procedure based on these concepts and their interlinkages is discussed based on specific examples.

A new approach based on input-output (IO) analysis has emerged to estimate the carbon footprints of companies and their products from cradle to gate. While they rely on the same principles as the GHG Protocol, they use a distributed iterative framework to improve the footprint estimations and reduce their uncertainty. While optimal estimations would result if all the world’s companies would enter such a system, this paper shows how such a distributed system could apply to the real world where many enterprises would stay out of the system. We show how it would increase the quality of the estimations with respect the GHG Protocol by integrating scope 1 and scope 2 data of the value chains in the footprint estimations and reducing the part of remaining scope 3 data. To help analyzing uncertainty, we show how to use the scope 1/2/3 decomposition to estimate the biases and the standard deviations of the computed production intensities. We illustrate the model on macroeconomic data for 44 sectors and two regions (Europe and Rest of World), using the Inter-Country Input-Output database (ICIO). Such a system would necessarily rely on Information and Communication Technology since the companies would be permanently interconnected in a large-scale meshed network, using an application protocol for data exchange.

As technology continues to play a central role in shaping global industries, the performance of technology firms on the NASDAQ has significant implications for broader economic trends. Investors, facing an increasingly complex landscape, require detailed insights to make informed decisions and navigate market volatility. Moreover, amid the ongoing digital transformation, understanding the operational dynamics of technology companies is critical for policymakers and regulatory bodies to create frameworks that foster innovation while ensuring market stability. In the current context, characterized by rapid technological advancements, market uncertainties, and evolving consumer demands, the need for a comprehensive study on the operational efficiency of NASDAQ-listed technology companies is more pertinent than ever. Objective of our study is to identify relationships and patterns among selected financial metrics to assess the operational efficiency of NASDAQ-listed technology companies between 2011 to 2023. Financial metrics used in the study include following variables namely revenues, cost of goods sold, operating expenses, research, and development expenses, selling and general administrative expenses, and operating income. Johansen's cointegration methodology is employed to unveil long-term relationships and equilibrium adjustments among the considered variables. Results of our study underscore the paramount importance of efficiently managing the cost of goods sold (COGS) for achieving superior operating performance among these leading technology firms. The findings point to a nuanced interplay among these operational metrics, highlighting the interconnectedness and sustained relationships among them. This suggests that the top technology companies exhibit a sophisticated understanding of the dynamics between these variables, allowing them to navigate the complexities of the industry with strategic finesse.

The transport sector is pivotal and indispensable in our daily existence, being the exclusive conduit for the intercontinental conveyance of commodities and individuals. Hence, comprehending the phenomenon of business failure within the transport industry assumes paramount significance in delineating an effective competitive policy for this sector. The primary objective of this research paper is to execute a comparative investigation between statistical models forecasting business failure and models founded on artificial intelligence, within the context of the transport sector. This analysis spans the temporal expanse from 2014 to 2021 and encompasses the nations of Portugal, Spain, France, and Italy, aiming to ascertain superior efficacy among these models. The dataset employed for this endeavor encompassed a final cohort of 4866 companies, comprising 2881 that endured as going concerns and 1985 that succumbed to business failure. The models developed for this study exhibited the capacity to accurately categorize a proportion of companies ranging from 71% to 73%. Nonetheless, upon comparative scrutiny of these outcomes with those derived from the statistical models dedicated to business failure prediction, it becomes evident that the latter demonstrate an enhanced predictive prowess, manifesting fewer errors in the classification of the scrutinized companies.

The state of epidemic emergency in force in our country since March and the related requirement to implement various sanitary procedures constitute problems for the operation of all companies. However, the unique operation of underground mining companies increases their scale considerably. However, despite initial turbulent moments related to the occurrence of an unknown threat, it was possible to stabilise the situation in all such companies as a result of implementing various anti-threat actions. Following the initial introduction to basic properties of the SARS-CoV-2 coronavirus, the paper presents the results of the study (a case study) on actions taken in individual mining companies. There was an attempt to formulate the so-called good work practices recommended to be applied.

Developing prosperous and inclusive societies requires a reformulation of the business-society nexus toward sustainability. This means that all economically motivated behaviors of firms need to also consider their social and environmental impact, and all social and environmental policies need to also consider their impact on the economy. With the Companies Act 2013, the Indian government adopted a legislative approach to reconfigure the business-society nexus. Mandating what has been considered discretionary elicited an extensive academic debate. We employ Content Configuration Analysis on 70 local and international English-language book chapters, research articles, reports, reviews, and expert commentaries published between 2013 and 2019 to develop a typology of the advantages and disadvantages associated with the Companies Act 2013. We find that, among the large set of arguments for and against the Act, specific arguments extolling its advantages concurrently appear as disadvantages in other texts. This paradox is indicative of the difficulties of satisfying stakeholder expectations, as well as the complexities corporate responsibility programs face in India. By systematizing the opportunities and challenges associated with the Companies Act 2013, we reveal how, similar to China, context and culture influence India’s socioeconomic development trajectory beyond the conventional market economy canon.

The UK food industry faces significant challenges to remain sustainable. With major challenges such as Brexit on the horizon, companies can no longer rely on a low labour cost workforce to maintain low production costs and achieve economic sustainability. Smart Systems (SS) is being seen as an approach towards achieving significant improvements in both economic and environmental sustainability. However, there is little evidence to indicate whether UK food companies are prepared for the implementation of such systems. The purpose of this research is to explore the applicability of Smart Systems in UK food manufacturing companies and, to identify the key priority areas and improvement levers for the implementation of such systems. A triangulated primary research approach is adopted and includes a questionnaire, follow up interviews and visits to thirty-two food manufacturing companies in the UK. The questionnaire and interviews are guided by the development of a unique measuring instrument created by the authors that is focusses upon SS technologies and systems. This paper makes an original contribution in that it is one of few academic studies to explore the implementation of SS in the industry and, provides a new perspective on the key drivers and inhibitors around its implementation. Findings suggest that the current turbulence in the industry could be bringing food companies closer to the adoption of such systems, hence it is a good time to define and develop the optimum SS implementation strategy.

The purpose of this paper is to examine if there are links between interpersonal trust and competences, relations and cooperation in Polish telecom companies. It examines what factors affect trust in coworkers and managers in sustainable organizations. The paper surveys a sample of 175 employees of telecom companies in Poland by means of a questionnaire. The results indicate that the competences, relations and cooperation are related to interpersonal trust. Regression analysis showed that the competences and relations predict a significant variance in trust amongst coworkers. Additionally, cooperation contributes to prediction of trust in mangers. Given the importance of trust in sustainable organizations, a better comprehension of what factors are related to team confidence provides valuable information for stakeholders. The results provide valuable clues how to improve interpersonal trust in sustainable organizations.

The paper presents the findings of research on companies in the early stage of development based on the concept of ensuring their sustainability. The starting point is attributes shaping a sustainable model of start-ups. A solution has been proposed and examined that identifies the factors dynamising a business model, which give the company the ability to make fast changes in the configuration of the business model, and that applies stabilizing factors based on the concept of the Triple Bottom Line. The research problem is a response to the phenomena of the bankruptcy of many start-ups that cannot find a way to survive in the long term. The business models of companies in the early stage of development should be designed taking into account the possibility of their dynamic and iterative changes when the earlier assumptions do not work when implemented in practice. A cognitive gap has been observed as the relevant literature does not propose a systemic solution to the problem of instability of the startups viewed from the perspective of the business model concept. The research problem, therefore, is to identify potential new methods to ensure the sustainability of young companies trying to combine aspects dynamising changes in business models, taking into account economic, environmental and social aspects. The findings of research on companies in the early stage of development show that when the methods of increasing the flexibility of the business model are applied and attention is drawn to environmental and social activities and a strong emphasis is put on financial performance, reflecting the expectations of shareholders, the concept of ensuring the sustainability of young companies from the point of view of sustainable business model attributes emerges.

The perceived poor performance of publicly traded companies on their sustainability commitments and the quality of sustainability reporting has prompted stakeholders to consider the economic, environmental, and social impacts of corporate activities. Economic activities have led to various threats in the form of climate change, pollution, greenhouse gas emissions, natural disasters, and other issues that have negatively impacted the environment and stakeholders. Companies are expected to report to stakeholders on their sustainability performance, but reality proves that present reporting falls below stakeholders’ expectations mainly due to its still voluntary nature. The present study aims to provide a literature review of the relationship between sustainability reporting and the role of companies governance, especially observing if climate change requirements and energy-needed changes are being accounted. Results highlight mixed evidence for the influence of board governance attributes, providing interesting insights for research advancement. The study has practical implications for businesses, regulators, governments, and other stakeholders in their policy deliberations and investment decisions. Further empirical studies are recommended to re-examine sustainability reporting using the variables identified as important factors and gaps in this study and other board characteristics to improve the generalizability of the results.

The use of the voice of the customer as a main input to guide decision making towards customer centricity strategies has become a necessity for companies. This research proposes a structured method of textual processing using the KDD (Knowledge Discovery Databases) methodology applied to the tweets of users of Colombian public sector companies, through the analysis of temporal sentiments and topic modeling to identify the areas in which actions should be taken to improve the perception of service. To fulfill such purpose, tweets from January to June 2022 are processed, followed by a temporal analysis of the evolution of the sentiment based on 3 enriched dictionaries; after, the LDA (Linear Discriminant Analysis) algorithm is implemented to find the areas with ailment for the user, in addition to propose a method to homologate the CIER (Comisión de Integración Energética Regional) survey. Finally, metrics are detailed to follow up the perception of the service. It is concluded that for the Acueducto the topic with the highest number of complaints is related to "Water truck request", for Enel "Servide Outages" and for Vanti: " Case solution and request information". Also, the homologation of 3 of the 5 pillars on which the CIER survey is based is presented.

This paper proposes a model to evaluate business projects to get into an incubator, allowing to rank them in order of selection priority. The model combines the Momentum method to build prospective scenarios and the Multiple Criteria Decision Making (MCDM) method TOPSIS-2N to rank the alternatives. Six business projects were evaluated to be incubated. The Momentum method made it possible for us to create an initial core of criteria for the evaluation of incubation projects. The TOPSIS-2N method supported the decision to choose the company to be incubated by ranking the alternatives in order of relevance. Our evaluation model has improved the existing models used by incubators. This model can be used and / or adapted by any incubator to evaluate the business projects to be incubated. The set of criteria for the evaluation of incubation projects is original and the use of prospective scenarios with a MCDM method to evaluate companies to be incubated does not exist in the literature.

This study examines the effect of market risk on the financial performance of 31 non-financial companies listed on the Casablanca Stock Exchange (CSE) over the period 2000-2016. We utilize three alternative variables to assess financial performance, namely return on assets, return on equity and profit margin. Next, we use the degree of financial leverage, the book-to-market ratio, and the gearing ratio as market risk variables. Besides, we employ the pooled OLS model, the fixed effects model, the random-effects model, the difference GMM and the system GMM models. The results show that market risk indicators have a negative and significant influence on the companies' financial performance. The elasticities are greater following the book-to-market ratio compared to the degree of financial leverage and the gearing ratio, respectively. In most cases, the firm size, the tangibility ratio, and the cash holdings ratio have a positive effect on financial performance, whereas the firms' age, the debt-to-income ratio, stock turnover, and leverage hurt the performance of these non-financial companies. Therefore, decision-makers and managers should mitigate market risk through appropriate strategies of risk management, such as derivatives and insurance techniques.

This paper aims to assess whether the financial performance of Portuguese companies that publish sustainability reports (SR) differs from the financial performance of companies that do not publish SR. We use two methodological procedures. First, we conducted a univariate analysis to test the differences in the financial performance according to the disclosure of SR. Second, we conducted a multivariate analysis using a multiple linear regression that explains financial performance by the disclosure of SR, as well as control variables such as sector, size, leverage, growth, and liquidity. Findings indicate that financial performance of companies that disclose SR does not significantly differ from the financial performance of companies that do not disclose SR. The results are robust to both methodological procedures, as well as to the sample split by sectors.

The following article analyzes Italian companies with more than 10 employees that use online sales tools. The data used were acquired from the ISTAT-BES database. The article first presents a static analysis of the data aimed at framing the phenomenon in the context of Italian regional disparities. Subsequently, a clustering with k-Means algorithm is proposed by comparing the Silhouette coefficient and the Elbow method. The investigation of the innovative and technological determinants of the observed variable is carried out through the application of a panel econometric model. Finally, different machine learning algorithms for prediction are compared. The results are critically discussed with economic policy suggestions.

Rising raw material prices can have a significant impact on the financial performance of the food and beverage (F&B) business. The purpose of this study was to determine the impact of rising prices of staples onfinancial resilience F&B business in Indonesia. This study uses a quantitative approach with bivariate correlation analysis and secondary data from the financial reports of F&B companies listed on the Indonesia Stock Exchange for the 2020-2022 period. The results showed that the increase in the price of basic commodities had a significant positive impact onfinancial resilience F&B company. This can be seen from the decline in the profitability and liquidity of F&B companies as a result of the increase in the price of basic commodities. Therefore, F&B companies must pay attention to and manage the risk of rising prices of basic commodities to maintainfinancial resilience and sustainable business continuity.

The dynamic global automotive sector is characterized by an ever-evolving demand for high-quality vehicles and accessible prices. This research tackles the issue of scrap reduction in electric motor manufacturing for the automotive industry, specifically in a Chinese company, by employing the PDCA methodology. The paper delves into the company's background and current landscape, while pinpointing the problem: specific production lines segments experiencing hi-pot issues are the primary source of scrap. The overarching goal is to design and implement a strategy that, leveraging the PDCA approach, reduces scrap generated during the eight-months subassembly (armature) manufacturing process, from its current average of 2.92% to 0.7%, ultimately enabling the company to eliminate hi-pot defects.

This study aims to understand the changes in management trends among global companies before and after the onset of COVID-19. To achieve this, we employed keyword and topic modeling to analyze 420 CEO messages extracted from the reports of the Fortune Global 100 largest companies. The analysis revealed a noteworthy prevalence of keywords associated with shared culture, such as face-to-face interactions and cooperation, during the initial period. In the subsequent period, we observed a higher frequency of keywords related to community-centeredness and digital trans-formation, including employee health and well-being, inequality reduction, and sustainable cities. Furthermore, we identified common topics before and after COVID-19, such as risk management and competitive advantage. However, the topics that exhibited variation were the significance of corporate leadership and the evolution of digital technologies. This study is significant in that it enables us to analyze CEO messages and deduce the trajectory of corporate management post-COVID-19.

The effective implementation of a sustainable supply chain leadership (SSCL) strategy at each organization’s level, positively impacts on corporation’s competitive advantage and sustainable development. While fears have been acknowledged in previous literature, the benefit of designing Sustainable supply chain models for operational excellence and sustainable development is a noteworthy exploration. The study collected statistical data using an online Survey- monkey questionnaire from 46 of the top 100 JSE-listed companies with the intention to elucidate the large firms’ transition from longstanding linear approaches to sustainable production and consumption to a more circular approach. A bivariate data analysis was used to generate the results in SPSS. The results indicate a positive contribution of SSCL strategy to operational excellence and sustainable development of large corporations if only the entire supply chain system is well-coordinated and implemented. This study makes a vital contribution by proposing a new SSCL model for fast-tracking corporate sustainability and enhancing corporate contributions to sustainable growth.

This research was conducted with the aim of knowing how to compare the financial performance of the oil and gas trading industry with cross-sectional analysis techniques. The type of research conducted in this research is qualitative research with research objects at several companies, namely PT Radiant Utama Interinsco Tbk, PT Elnusa Tbk, PT AKR Corporindo Tbk, and PT Aneka Gas Industri Tbk. The data used in this study comes from secondary data, namely the internet in the form of company financial reports for the 2019-2021 period obtained from the Indonesia Stock Exchange. The results of this study indicate that PT Radiant Utama Interinsco Tbk has the best financial performance on inventory turnover ratio and average age, PT Elnusa Tbk has good inventory performance on current ratio, quick ratio, DAR, and DER., PT AKR. Corporindo Tbk has performed well on the ratios of TIE, FCC, Dividend Payout, Dividend Yield, and PER. PT Aneka Gas Industri Tbk has performed well on the ratio of Receivables Turnover Ratio and Average Age of Receivables.

The coronavirus 2019 (Covid-19) pandemic has emerged as a global phenomenon that significantly affects almost all sectors, irrespective of whether they have a well-established economic system. The inception of COVID-19 pandemic has increased and accelerated the demand for opera industry embrace digit technology to continue to produce performances and reach audiences. The brutality of the Covid-19 pandemic has affected most sectors, and opera artists are significantly affected in the Global South. South Africa, among others, is at the receiving end. The Covid-19 pandemic has wreaked havoc and exacerbated the existing vulnerability of opera artists. Opera artists have difficulty obtaining employment and finding funding for performing arts organisations have caused seriously challenged opera artists to survive during the Covid-19 pandemic. This study is aimed to examine the quest for new digital skills for opera artists and opera companies during the Covid-19 pandemic. A qualitative research method was adopted using interviews with opera artists, selected retired opera practitioners and managers of opera companies. In this study, scholarly documents were reviewed to yield trustworthy findings. The findings demonstrate a high demand for opera artists to upgrade their current skills to meet the demand for digital skills. This demand for digital skills is partially attributable to the closed and suspension of live theatre performances due to the Covid-19 pandemic. The findings also reveal that digital connectivity in the performing arts sector become an essential driver of economic growth. This study concludes by affirming that digital skills are key skills required for resuscitating the opera industry.

This study aims to examine Turkish companies from a sustainability and green innovation point of view. Through this purpose, this research’s objective is to find out relationship between sustainability drivers and green innovation and also to search for green organizational culture’s mediation effect in this relationship. Survey was carried in companies operating in Turkey which were listed among İstanbul Chamber of Industry (ICI) Top 500 companies for last 3 years successively and have ISO14001 Environmental Management Certificate. According to the survey results, it was manifested that factors directing companies to sustainability having a positive relationship with green organizational culture and green innovation. It is found that there is a partial mediation effect of green organizational culture between motivating factors for sustainability and green innovation.

One of the most important objectives of the studies worldwide is to improve the performance of automotive engines to reduce fuel consumption and environmental pollution. Accordingly, the principal motivation of this research study is improving the tribological behavior of the piston ring/cylinder liner interfaces as a promising and straightforward approach in automotive fuel economy and increasing engine durability using Al₂O₃ and TiO₂ nanomaterials as smart nano-lubricant additives that adapted to different operating conditions by replenishing mechanisms anti-friction and anti-wear in automotive engines.

Without doubt, the social and environmental business impact will become more important as the governments cannot take care about these problems. Thus, launching the EU Green deal rules, World Global Sustainable Development Goals, corporate social responsibility (CSR) activities and strategies are part of this global commitment. Additionally, CSR is strongly connected to the exploration of (social) market awareness and technology development and application as it focusses on social, environmental and economic business impact. The main goal of the paper is to verify that contemporary greener CSR strategies are beneficiary activity for high-tech companies because of better competitive advantages acquisition through management of corporate reputation risk and patenting innovative technologies. The structure of the paper is the next: 1. Introduction – explanation the previous researches that explore the relation: CSR strategy – high-tech company competitiveness; 2. State of art – exploring the corporate reputation and patent rights as factors in CSR strategy; 3. Patent monopoly and CSR – research the connection between reputation risks of patents rights and CSR strategy; 4. Business performance and CSR reporting – briefly research methodology is presented as some results from Bulgarian companies; 5. Discussion and conclusions – summarizing a methodology for patent rights and reputation risk management for better CSR effects.

This study aims to analyse whether Chinese companies' R&D investment affects management innovation performance. Also, this dissertation defines management innovation as diversification strategies such as technology and industry diversification and analyzes the impact of these diversification strategies. In particular, this paper analyzes whether R&D investment leads to technology and industry diversification and whether technology diversification creates a mediating effect in the process of R&D investment leading to industry diversification. The analysis results can be summarized as follows: First, R&D investment showed a significant positive relationship with industry diversification. Second, R&D investment shows a significantly positive relationship with technology diversification. Third, technology and industry diversification showed a positive relationship. Fourth, this study examined the mediating role of technology diversification, and it was confirmed that technology diversification plays a mediating role in the effect of R&D investment on industry diversification. R&D investment and business innovation play a key role in the sustainable development of enterprises, and the findings of this paper have important reference value for enterprises' R&D investment decision-making. The results of this study provide the following implications that Chinese companies improve business innovation performance by increasing their R&D investment, promoting innovative R&D, and improving technology diversification and industry diversification strategies.

Numerous studies have been conducted in past so as to understand whether the working capital management policies of an organisation affect its performance or not. Some studies have found a positive relationship between WCM and firm performance. However, other studies have found a negative impact of WCM on firm performance. Present research work is an endeavour in this direction to find out the working capital management policies and strategies of Indian cement companies and their performances. The study employs a quantitative approach to examine whether the Indian cement companies optimally use their working capital, which is analysed by establishing the relationship between the working capital management and profitability using 11-year (2010-2021) financial data of 31 cement companies listed in Bombay Stock Exchange (BSE). The findings of the random-effects model say that only ITP is significantly negatively related to the ROA of the cement companies at a 0.01 level of significance. Similarly, APP also negatively yet poorly predicts ROA at a 0.10 level of significance the firm’s profitability is not significantly affected by ARP and CCC. Also, it has been observed that the liquidity measures CR and QR have a significant positive association with ROA. Further, the size of the industries and leverage are inversely related to ROA but the age of the firm is not significantly predicting their financial performance.

This paper investigates if Corporate Social Responsibility (CSR) reports published by a selected group of Nordic companies are aligned with the Global Reporting Initiative (GRI) standards. To achieve this goal, several natural language processing, and text mining techniques were implemented and tested. We extracted strings, corpus, and hybrid semantic similarities from the reports and evaluated the models through the intrinsic assessment methodology. A quantitative ranking score based on index matching was developed to complement the semantic valuation. The final results show that Latent Semantic Analysis (LSA) and Global Vectors for Word Representation (GloVE) are the best methods for our study. Our findings will open the door to the automatic evaluation of sustainability reports which could have a strong impact on the environment.

The purpose of this article is to draw attention to the challenges faced by business organizations implementing sustainable solutions in the United Arab Emirates (UAE) and the wider Gulf Coast Countries (GCC) region. To this end, our study examines an academic theory supporting the implementation of responsible solutions to the market. Ultimately, the authors hope to inspire the reader to consider what he or she can do to ameliorate the existing challenges encountered by sustainable businesses. The analysis presented in this article implies that in recent markets, the implementation of the sustainability theory is essential for further development. The research project contributes to the increase of knowledge about corporate and organizational challenges related to running a responsible business, as well as challenges related to the application of environmental, social and economic aspects of sustainable business practices. The research is currently limited to conceptual analysis, literature review and a survey conducted during the Sustainability Week 2019 in Abu Dhabi, United Arab Emirates. Nevertheless, this is the first stage of the research project conducted by the research team in cooperation with enterprises that implement responsible solutions in many global markets, and in UAE market. The scope of the first stage of the study was limited to the analysis of data clarifying the concept of the model specified in the research. To prove the validity of the model it will be implemented and tested in cooperation with organizations participating in the research.

While the importance of corporate governance has been broadly acknowledged in global financial markets and academic research, how to devise a practical evaluation system is relatively unexplored. This paper attempts to refine the Corporate Governance Evaluation System (CGES), constructed by the Taiwan Stock Exchange (TWSE) since 2014. The current CGES has several debatable issues in its complicated design (e.g., it comprises over 80 indicators in different types). To resolve those issues, this study invited ten senior domain experts (including several CEOs of financial holding companies) to retrieve 13 essential criteria from the CGES in four dimensions. And this study integrates several multiple criteria decision-making (MCDM) methods (i.e., Decision-making trial and evaluation laboratory (DEMATEL), modified VIKOR, DEMATEL-based analytical network process (DANP)) and the fuzzy evaluation technique to rank the exemplary companies. The obtained ranking is consistent with the one released from the CGES in 2017. This study conducted additional experiments to ensure the robustness of the findings. The newly devised model not only supports the ranking decisions but also provides a managerial guidance for companies to pursue systematic improvements. These findings enrich the understanding of corporate governance and contribute to gaining business sustainability for financial holding companies.

Knowledge-based approaches are useful alternatives to predict the Failure Probability (FP) coping with the insufficient data, process integrity, and complexity issue in manufacturing systems. This study proposes a Fault Tree Analysis (FTA) approach as proactive knowledge-based technique to estimate the FP based maintenance planning with subjective information from domain experts. However, the classical-FTA still suffers from uncertainty and static structure limitations which poses a substantial dilemma in predicting FP. To deal with the uncertainty issues, a Fuzzy-FTA (FFTA) model was developed by statistical analysing the effective attributes such as experts' trait impacts, scales variation and, assorted membership and defuzzification functions. Besides, a Bayesian Network (BN) theory was conducted to overcome the static limitation of classical-FTA. The results of FFTA model revealed that the changes in decision attributes were not statistically significant on FP variation while BN model considering conditional rules to reflect the dynamic relationship between events had more impact on predicting FP. After all, the integrated FFTA-BN model was used in the optimization model to find the optimal maintenance intervals according to estimated FP and the total expected cost. As a practical example, the proposed model was implemented in a semi-automatic filling system in an automotive production line. The outcomes could be useful for upgrading the availability and safety of complex equipment in manufacturing systems.

The concept of supply chain leadership strategy has garnered increasing interest from policymakers and experts, because it is among the most dependable practices to sustainable innovation and competitiveness for large firms across developing economies. Effective implementation of supply chain leadership strategic actions at each level in the company can create sustainable innovative and competitiveness. The study collected statistical data using an online Survey- Monkey questionnaire from 46 of top 100 JSE-listed companies with the intention to discover supply chain leadership strategic actions that drive sustainable innovation and competitiveness in the company. The findings expose a significant empirical insight for companies to understand and leverage supply chain leadership strategic actions to influence sustainable innovative position in a developing economy. These results suggest that firms operating within emerging markets should embrace and acknowledge the importance of sustainable innovation in business practices in the provision of goods and services. This study therefore delivers major contributions to the literature to assist in planning sustainable innovation and supply chain practices in a developing economy to survive in a competitive global environment. The paper also offers a vigorous awareness and knowledge of the common characteristics and strategies for supply chain management that needs to be prioritized by the JSE-listed companies.

The service sector, whose value has started to increase in recent years, has gained momentum with the acceleration of economic developments especially after the 2000s in Turkey. In a world where competition is increasing and social purchase perception is changing, companies started to differentiate in the service sector to create a competitive advantage. Companies that would like to grow in the industry and aspire to a greater proportion need credit to extend. There are many factors to consider in order to allocate the credit. Banks make financial and non-financial analysis to make credit decisions. This study has been prepared to assess the effect of financial and non-financial features of middle segment companies that need credit in the service sector on the credit decision to be allocated by banks. The group of variables that explain the credit decision at the highest level in these companies are non-financial variables.

The COVID-19 pandemic had a wide-ranging impact, resulting in a global recession due to weakened purchasing power. This circumstance necessitates business organizations adapting to developments and being more conscious of the risk of financial statement fraud. The intention of this research is to investigate the way corporate governance affected financial statement fraud during the COVID-19 pandemic. To acquire empirical data for examining corporate governance variables on financial statement fraud, the research was examined using quantitative methods. The study takes advantage of secondary data acquired from annual reports of companies under special monitoring listed on the Indonesia Stock Exchange of 2020-2021. The logistic regression method was used to evaluate 134 data sets, and financial statement fraud was measured using the Z-Score and F-Score models. The results indicate that using the Z-score, only the board size has a negative effect on financial statement fraud during the COVID- 19 pandemic. Meanwhile, using the F-Score, the corporate governance variables studied are not proven to have an influence on financial statement fraud during the COVID 19 pandemic.

(1) As the craft beer industry continues to expand in Canada, understanding the regional differences between the Eastern and Western markets becomes pivotal for brewing ingredient companies seeking to penetrate or expand within these regions. This study aims to provide a comprehensive review of these two distinctive markets, focusing on economic, logistical, ingredient, and cultural differences. (2) The study primarily relies on secondary data from government, industry reports, and scholarly publications, providing a holistic view of the Canadian craft beer landscape. It further highlights the need to consider market distinctions between Canada and the United States. (3) Findings reveal that Western Canadian breweries, unlike their Eastern counterparts, operate under constrained storage space, prefer locally-sourced ingredients, and offer a distinct variety of beer styles catering to local tastes. The study further uncovers the regulatory and financial complexities of the Canadian market compared to the United States. (4) Based on these findings, this study provides strategic recommendations for brewing ingredient companies, emphasizing domestic logistics, local sourcing, product adaptation, educational support, and regulatory navigation, fostering success in the Canadian craft beer landscape.

The purpose of this study was to evaluate the financial performances of the publicly held healthcare companies in crisis periods in Türkiye. The 2018 Economic Crisis and the COVID-19 pandemic crisis were included in the study as the crisis periods. We collected the financial data of the publicly held healthcare companies and calculated three liquidity, three turnover, three leverage and three profitability ratios by ratio analysis to use as financial performance indicators. We then conducted Wilcoxon signed-rank tests and we did separate analyses for the 2018 Economic Crisis and the COVID-19 pandemic crisis. The results of the analyses showed that there were no statistically significant differences between the publicly held healthcare companies’ liquidity, turnover, leverage, profitability ratios and thus their financial performances before the crises and after the crises. While the results are reassuring and give valuable insights to managers and policy makers to determine the areas that needs to be strengthened to be better prepared for possible future crises, our sample was limited. Therefore, this study presents an exploratory foundation for future studies which are needed to make a case of financial stability for the publicly held healthcare companies before and after the crisis periods.

The study is based on the notion that big data predictive analytics is important for developing strategic alliances performance of companies. this study investigates the relationship between big data predictive analytics, big data culture, and competitive strategies 'techniques were adopted, such as descriptive statistics, correlation,regression, etc. using SPSS and SmartPLS statistical software. Hypotheses were tested with bootstrapped analysis using SEM (through SmartPLS). The study developed a structural equation model by using the SEM analysis. The results of the SEM analysis suggested the hypothesized model of the study was valid. The results supported all the hypotheses of the study.Through empirical analysis, demonstrated the conclusion is that the big data predictive analytics has a positive and significant relationship with strategic alliance performance

A tailored model for the assessment of environmental benefits achievable by “light-weighting” in the automotive field is presented. The model is based on the Fuel Reduction Value (FRV) coefficient, which expresses the Fuel Consumption (FC) saving involved by a 100 kg mass reduction. The work is composed of two main sections: simulation and environmental modelling. Simulation modelling performs an in-depth calculation of weight-induced FC whose outcome is the FRV evaluated for a wide range of Diesel Turbocharged (DT) vehicle case studies. Environmental modelling converts fuel saving to impact reduction basing on the FRVs obtained by simulations. Results show that for the considered case studies, FRV is within the range 0.115–0.143 and 0.142–0.388 L/100 km × 100 kg, respectively, for mass reduction only and powertrain adaptation (secondary effects). The implementation of FRVs within the environmental modelling represents the added value of the research and makes the model a valuable tool for application to real case studies of automotive lightweight LCA.

In a business environment that is constantly changing, intellectual capital stands out as the most valuable asset for companies. Those who invest in developing their employees, especially their Chief Financial Officers (CFOs), tend to outperform their competitors. This study explores the relationship between the intellectual Capital of CFOs and the financial performance of companies listed on B3. The 100 companies with the largest capitalization listed on B3 in 2022 were analyzed, with available data on the CFO. A statistical model was applied in a cross-section analysis, considering two of the three subdivisions of Intellectual Capital: Human Capital ( experience, education, and certifications) and Relational/Social Capital ( network and reputation of the CFO). The results indicated a statistically significant relationship between CFOs' Human Capital level and the performance of the companies they manage, measured by EPS, ROA, and ROE. However, no statistical significance was found for Relational/Social Capital. This study contributes to the literature on intellectual capital and corporate finance in the Brazilian context, providing new evidence on the importance of CFOs' intellectual capital for company performance. It was observed that there are few equivalent studies in Brazil on the topic, especially about the Intellectual Capital of CFOs of companies listed on the stock exchange (BOVESPA).

This paper aims at providing a multisource data analysis, including direct data collection, focussed on daily average distances covered with motorised mobility. Its results can be used as a basis for policies involving a shift towards new propulsions, electric motors or hybrid electric vehicles (HEV) for road vehicles. A number of variables influence the propensity of drivers to acquire or use electric traction, even the option of plug-in hybrid electric vehicles (PHEV). This paper addresses one of such variable: the compliancy of electric traction regarding both hybrid plug-in solutions and full-electric vehicles, in addition to the autonomy of batteries (range), with the daily travels by road vehicles, mainly by automobiles. We want to understand whether the constraints leading towards a greater independence from crude oil rather than constraints concerning emissions, mainly in urban contexts, might be compliant with the habitual daily trips of drivers. We also want to understand if these daily trips have varied much during recent years and the consequences they may have on operational costs of plug-in automobiles. We are well aware that the average distances do not represent the actual daily runs of vehicles; yet similar distributions of daily distances for different case studies indicate that a high percentage of trips respond to certain features. After introducing a general overview of road-motorised mobility in Italy, the paper compares data from other studies to provide an indication of average daily driving distances. This reveals how different recent analyses converge on a limited range of average road distances covered daily by Italians, which is compliant with ranges allowed by electric batteries, provided that their low energy density in comparison with that of oil-derived fuels do not imply a significant increase in vehicle mass. Subsequently, average distances in some EU Countries are taken from the literature, and the results are also compared with U.S. data. The study extends the analysis of trends on the use of automobiles and road-vehicles to the international context by also addressing average daily distances covered for freight transport in some EU Countries, thereby providing a further basis for comparison and for understanding whether the daily motorised mobility can be considered as a stable phenomenon. Finally, an analysis is provided of the economic operational advantages from using plug-in vehicles. The main aim of this paper is thereafter to investigate the average daily motorised mobility of single vehicles – so not an aggregated motorised mobility as collected by some statistics – by using private motorised vehicles in Italy, with related trends; thereafter, to compare these data with those obtained from other countries, making use of both existing research studies and directly collected data; the final aim is to understand both the compliance of daily activities based on the use of automobiles with the autonomy of batteries (range) and to calculate some economic outcomes.

The purpose of this article is to present the COVID-19 pandemic disruptions occurring in the supply chain of automotive companies, taking into account the type of business. The specific objectives are: to identify and characterise the types of enterprises operating in automotive supply chains, to identify changes during the pandemic in automotive enterprises, depending on the type of activity, to show disruptions in automotive supply chains and ways to counteract these disadvantages depending on the type of activity. Automotive enterprises operating in Poland were selected for the study purposefully. A random selection method was used to select 500 automotive companies for the study. The data sources were surveys conducted in June 2023 among 500 enterprises in the form of a face-to-face telephone interview. Automotive companies experienced supply chain disruptions, regardless of the type of business. Most often, these were caused by lockdowns and official closures, low stocks of materials and products, and problems with employees. There was no difference by type of business. Disruptions were most often short-lived, up to 1 year. Companies countered disruptions by using mostly operational measures, which were short-lived. Only a small percentage of operators made strategic decisions and countered disruptions over a longer period. The scale of these actions was greater among manufacturers than among dealers and car service companies.

Logistics industry has been found to be among the key sources of carbon emission. In Vietnam logistics industry, there is a considerable difference between the number of foreign and Vietnamese firms as well as the proportion of markets that they are taking. This study is to research the low-carbon emission measures conducted by domestic and foreign invested logistics service providers (LSPs) and compare the results of the two groups. Both qualitative and quantitative approaches are applied. Literatures in relevant fields are reviewed and expert opinions are taken for structuring a questionnaire which was later distributed to 279 LSPs, with 166 returned and 159 being valid for data calculation. The results imply that there are differences in extension of applications of low-carbon practices between foreign and domestic firms. Except for transport mode switch and energy-saving lighting, the other practices witness that adoption levels of foreign LSPs are higher than their counterparts, which is possibly thanks to their global operation, more comfortable capital resources and awareness level of green initiative necessity. In conclusion, a comparison between the application conducted by foreign-invested firms and domestic ones, which has not been investigated before, was made.

In this dynamic 21st Century global economy, managers of insurance companies cannot afford to ignore the involvement of their employees in strategic change programmes. The employee's voice in strategic change programmes is now a prerequisite for organizational performance. This study seeks to determine the effect of employee involvement in strategic change programmes through participation in decision-making, teamwork, communication, creativity, and innovation. The research approach used was quantitative to collect data from 115 respondents using a 5-point Likert scale questionnaire. The study employed the multiple regression method to analyse data using the IBM SPSS V28 software. All five constructs of employee involvement had a significant effect on the performance of insurance companies in Zimbabwe. The study findings will convince top managerial leaders of the insurance industry to acknowledge and appreciate the importance of involving employees in strategic change programmes. Besides, industry regulatory authorities can advocate for policies that encourage employee involvement in decision-making.

Research has shown that innovativeness is a key factor leading to company performance. However, the business environment can play a detrimental effect on company performance by undermining the company’s internal strategic efforts in terms of innovativeness. To test this, 344 questionnaires were sent to manufacturing companies owners and managers. 178 of them were returned and usable to test the study hypotheses. Though a hierarchical regression analysis, it was found that innovativeness has positive and significant effect on company performance, but business environmental dynamism has a negative and significant effect in innovativeness-company performance relationship. Recommendations and other research perspectives are suggested

This study focuses on a sample of Chinese listed companies from 2019 to 2020 to explore the relationships among corporate social responsibility, financial constraints, and financial performance. In addition, we discuss five factors affecting financial constraints. We also analyze the types of enterprises that can improve their financial performance by implementing corporate social responsibility keeping in mind the factors that lead to a high degree of financial constraint. The results indicate that: 1. The degree of financial constraints has a negative and significant impact on financial performance; 2. There is a reverse relationship between the degree of financial constraints and the effectiveness of corporate social responsibility measures; 3. Enterprises with high financial constraints (due to lower financial slack and revenue growth rates) can significantly improve their financial performance through the implementation of effective corporate social responsibility programs. 4. Enterprises with high financial constraints, caused by financial slack and revenue growth rate, can significantly improve their financial performance by implementing corporate social responsibility programs.