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The purpose of this paper is to examine the aerodynamic effects of rear spoiler geometry on a sports car. Today, due to economical, safety and even environmental concerns, vehicle aerodynamics play a much more significant role in design considerations and rear spoilers play a major role in this area.

A 2-D vehicle geometry of a race car is created and solved using the computational fluid dynamics (CFD) solver FLUENT version 6.3. The aerodynamic effects are analyzed under various vehicle speeds with and without a rear spoiler. The main results are compared to a wind tunnel experiment conducted with 1/18 replica of a Nascar.

By the CFD analysis, the drag coefficient without the spoiler is calculated to be 0.31. When the spoiler is added to the geometry, the drag coefficient increases to 0.36. The computational results with the spoiler are compared with the experimental data, and a good agreement is obtained within a 5.8 percent error band. The uncertainty associated with the experimental results of the drag coefficient is calculated to be 6.1 percent for the wind tunnel testing. The sources of discrepancies between the experimental and numerical results are identified and potential improvements on the model and experiments are provided in the paper. Furthermore, in the CFD model, it is found that the addition of the spoiler caused a decrease in the lift coefficient from 0.26 to 0.05.

This paper examines the effects of rear spoiler geometry on vehicle aerodynamic drag by comparing the CFD analysis with wind tunnel experimentation and conducting an uncertainty analysis to assess the reliability of the obtained results.

Complaint service management, aimed at improving customer satisfaction, provides important content for incorporation into studying a closed-loop supply chain. An analysis of the relationship between two provides the basis for probing the role of complaint management (CM) in the closed-loop supply chain to help it perform more efficiently and effectively through the application of advanced technologies. This paper considers how CM can be computed combining computer communication and information technologies. This computing process involves collection, evaluation and disposal. Using computer telephone integration technology, an integrated multi-channel system is designed; complaint and production evaluated through an intelligent decision support system; and CM processing system established to implement corresponding disposal which reflects the utility of CM. This research on the process of incorporating CM into our studies has significance for computing business service in the future. Based on exergoeconomics theory, the closed-loop supply chain is discussed, and the metric about “system negative environment effect” is introduced to system performance in terms of energy expenditures; a case study illustrates the efficacy of the process

The purpose of this paper is to survey the technical performance of the cement industry including those related to procedures; groundwork of raw materials, fuels and semi-finished products for processing; accessibility of machinery, plant and equipment for various operations; arrangement and process control management.

A broad range of survey and research was reviewed, and all revealed the methods to recognize the key influences for development of green technology. The study explores the present scenario of green manufacturing (GM) strategies of Indian cement companies and provides the industrial ecology, ways of reducing energy consumption, environmental impact data collection, design and control of manufacturing systems and integration of product and manufacturing system. It also reveals the problems in decision-making systems owing to the impact of the green product design. Here, in this paper, all information is obtained by the medium of internet, journals, articles, and magazines.

This paper describes a problem of global warming, gas, water and other wastages emissions at the time of cement manufacturing and put forward a path that enables decision makers to assess the perception of GM in their organization and in prioritizing GM efforts.

This perspective survey is to provide an integrative outlook of performance methods for GM practices in the Indian cement industries. It gives important information, which expectantly will help in cement industry to adopt GM practices. This paper fills the gap in the literature on identification, establishment, and validation of performance measures of GM for Indian cement industries.

The primary purpose is to empower financial institutions in AI integration decisions. By combining QSFS and the Golden Cut technique, the study establishes a robust foundation for assessing AI progress effects, aligning implementation with performance goals, and promoting technical innovation. Dimensions explored include AI-related workforce competency, technological adaption, and ethical AI practices, crucial components within the BSC framework for technological innovation.

This study employs a distinctive approach, integrating the Balanced Scorecard (BSC) framework with Quantum Spherical Fuzzy Sets (QSFS) and the Golden Cut approach to explore the dynamic landscape of AI deployment. The integration addresses uncertainties, enhancing impact assessment accuracy amid ambiguity associated with AI outcomes. QSFS and the Golden Cut technique together facilitate precise identification of thresholds and crucial values.

The research delves into the intricate relationship between enduring financial stability and AI progress, recognizing technology's crucial influence on financial decision-making. Findings underscore technology's significant impact on financial institutions' AI integration decisions. This novel approach provides a strong quantitative basis, offering insights into workforce competency, technological adaption, and ethical AI practices.

Despite valuable contributions, the study acknowledges limitations, such as potential biases and generalizability concerns, emphasizing the need for cautious interpretation and suggesting future research directions. Recognizing the research's boundaries and complexities in studying AI deployment in financial institutions underscores the need for ongoing exploration.

The research's originality lies in presenting an innovative methodology, integrating BSC, QSFS, and the Golden Cut, providing a unique perspective for decision-making. Contributions extend beyond academia, offering practical insights to enhance AI strategic implementation in the financial industry. This novel approach enriches the technology and finance discourse, fostering theoretical and practical advancements.

This study seeks to investigate whether firms’ capital structure decisions are congruent with the assumptions underpinning the traditional trade-off theory and the pecking order theory in Ghana. Using a sample of listed firms, the dynamic system generalized method of moments (GMM) technique is applied on a balanced panel data spanning 2008–2016. The findings reveal that the financing decisions of Ghanaian firms adhere to the pecking order theory, given the established relationship between leverage and profitability, firm age, as well as firm size. The study also shows that tax does not matter for corporate leverage, departing from the tax proposition of the traditional trade-off theory. However, the negative effect of growth opportunities and risk on debt corroborates the trade-off theory. Consequently, it is postulated that the trade-off theory and the pecking order theory are not discordant in predicting firms’ capital structure decisions in Ghana.

Today’s business environment has the nature that challenges the decision-making processes of businesses with its many different factors including technological developments and changing consumer structures. Previous research focused on specific contexts of the business environment regarding marketing and innovation issues, however, an integrative approach can be helpful for understanding and taking actions. This study aims to present a comprehensive framework which employs sensemaking from management literature as an approach to evaluate the market environment. Following a conceptual approach for the methodology, a framework consisting of three stages: discovery, sensemaking, and prediction is included in the study. Proposed framework identifies the stages for the sensemaking of consumers and can guide marketing decision-makers for competitiveness in the digital world.

The current study was developed in response to the profound impact of ethical practices on the beverage industry. It aims to examine the mediating role of perceived brand trustworthiness in the relationship between brand social responsibility and brand positioning in the Tanzanian beverage industry.

The study adopted a post-positivist approach, as it encompasses a deterministic perspective where causes are believed to determine outcomes or effects. The study focused on customers of two major beverage companies in Tanzania, namely Coca-Cola and Pepsi. Data were collected from 458 customers and analyzed using structural equation modeling.

The findings indicate that brand social responsibility serves as a valuable intangible asset, capable of establishing a competitive edge when integrated into the value proposition. Additionally, the results reveal that brand trustworthiness plays a mediating role in the connection between brand social responsibility and brand positioning.

The study employed a convenience sampling technique; hence, generalization of the findings should be approached with caution.

This study represents one of the few scholarly endeavors that explore the role of social responsibility at the product brand level in establishing brand positioning. By doing so, it contributes to the advancement of knowledge concerning the impact of brand social responsibility on building competitiveness within the context of today's competitive business environment.

The main purpose of this study is to provide a simple, efficient and economic system for saline wastewater treatment.

Industrial auditing was conducted to determine the water usage and wastewater characteristics during the manufacturing processes of pickling vegetables. In‐plant control measures were carried out prior to the end‐off‐pipe treatment. The treatment process was a simple pilot scale using two compartments alternated anaerobic fixed bed reactors (AAFBR).

The study indicated that applying the in‐plant control measures prior to final treatment of wastewater reduced the organic load and total suspended solids by almost 50 per cent. Post treatment of the end‐off‐pipe reduced the chemical oxygen demand, total suspended solids and dissolved salts by 84.2 per cent, 71 per cent and 52.4 per cent, respectively.

The proposed scheme was already implemented. The treated effluent from the factory was complying with the National regulatory standards for wastewater discharge into the public sewage network.

The purpose of this paper is twofold: first, to examine the differential effect of two cognitive (i.e. product experience, outcome focussed) and two emotional experiences (i.e. surprise and immersion) on customers’ cognitive outcomes (i.e. satisfaction, trust and value), and customers’ emotional outcomes (i.e. passion, connection and affection); and second, to test the differential effect of customers’ cognitive and emotional outcomes on switching resistance loyalty (SRL).

Survey data were collected from 843 respondents using an online panel in the UK. Structural equation modelling was employed to analyse the data (AMOS 18.0).

First, cognitive experiences had a more significant effect on customers’ cognitive outcomes compared to their effect on customers’ emotional outcomes. Second, emotional experiences had a more significant effect on customers’ emotional outcomes compared to their effect on customers’ cognitive outcomes. Third, the impact of customers’ emotional outcomes on SRL was not significantly higher compared to that of customers’ cognitive outcomes. Fourth, the indirect effect of cognitive experiences on SRL was significantly higher, compared to that of emotional experiences.

The key contribution of this research stems from examining the differential effect of cognitive and emotional experiences on different consumers’ cognitive and emotional outcomes, thus providing deeper insights into the nature of the relationship between such variables.