Finanční analýza společnosti P&G

This bachelor thesis concentrates on the financial situation of Procter & Gamble Company. The main objective of this bachelor thesis is using common-size analysis, financial ratio analysis and pyramidal decomposition to make financial analysis of Procter & Gamble Company and to assess Procter & Gamble Company’s operation. The analysis is based on data from Procter & Gamble Company’s financial statements from 2011 to 2016 combined with company’s history and big events. In theoretical part we explain the financial analysis theory and write the introduction of specific methods, which are common-size, financial ratio and pyramidal decomposition. In specific analysis, we use the methods mentioned in theoretical part to analyze the specific financial condition of the Procter & Gamble Company. Finally, we find that Procter & Gamble Company is still the leader of consumer goods market even if they are confronting troubles. Now it is at the turning point for the development of the company.This bachelor thesis concentrates on the financial situation of Procter & Gamble Company. The main objective of this bachelor thesis is using common-size analysis, financial ratio analysis and pyramidal decomposition to make financial analysis of Procter & Gamble Company and to assess Procter & Gamble Company’s operation. The analysis is based on data from Procter & Gamble Company’s financial statements from 2011 to 2016 combined with company’s history and big events. In theoretical part we explain the financial analysis theory and write the introduction of specific methods, which are common-size, financial ratio and pyramidal decomposition. In specific analysis, we use the methods mentioned in theoretical part to analyze the specific financial condition of the Procter & Gamble Company. Finally, we find that Procter & Gamble Company is still the leader of consumer goods market even if they are confronting troubles. Now it is at the turning point for the development of the company.154 - Katedra financívýborn

Changes of postmortem apoptotic factors, genes and proteins and their potential associations with beef tenderization

Apoptosis in postmortem muscle is a potential factor affecting meat quality. This study aimed to investigate the changes in apoptotic genes and proteins, reactive oxygen species (ROS), caspase-3 activity and their underlying relationship with meat tenderization. As postmortem time extended, there was a significant increase in myofibril fragmentation index (MFI) and destruction of muscle fibers. Oxidative stress deepened alongside the onset of apoptosis. Mitochondrial membrane potential (MMP) decreased, and caspase-3 activity increased during the first 24 h postmortem. Forty apoptotic genes displayed significant differences, involving DNA damage, autophagy, the death receptor pathway, the mitochondrial pathway, the Bcl-2 family, and the caspases family. The expression of most apoptotic genes was abundant in the early postmortem stage, enhancing the potential for early apoptosis. Apoptotic proteins of apoptosis-inducing factor, mitochondrion-associated 1 (AIFM1) and endonuclease G (ENDOG) showed the damage of apoptosis to DNA. Also, the decreasing expression of Bcl2 and increasing expression of Bak1 with time demonstrated the effects of mitochondrial apoptosis on postmortem muscle. These findings suggest that postmortem muscle apoptosis is a physiological process co-regulated by multiple genes, and potentially contributes to meat tenderization and quality

Essays on Consumer Information Acquisition in Marketing Channels

University of Minnesota Ph.D. dissertation. May 2020. Major: Business Administration. Advisor: George John. 1 computer file (PDF); vii, 104 pages.Overall, this dissertation employs game theoretical models to investigate consumer information acquisition. Its principal novelty is that I incorporate a richer supply structure with active retailers. This allows me to explore issues that are unique to the marketing channel. Essay 1: Prominent Retailer and Intra-brand Competition studies consumers’ active information acquisition patterns. Specifically, I investigate the interaction between active consumer search and retailers’ pricing decisions when the search share is disproportionally distributed. I am motivated by the phenomenon of “prominence”. That is, internet retail search traffic tends to be concentrated on a “prominent” retailer, such as Amazon in the United States or Alibaba in China. I develop a sequential search model to provide insights into the impact of prominence in an intra-brand setting. My research sheds light on (1) how a prominent retailer’s relative prices hinge on a threshold level of prominence, (2) the consequences of search traffic volumes on a retailer’s profit, and (3) the impact of search traffic concentration on competition and consumer welfare. Surprisingly, I find that more search traffic can reduce a retailer’s profit. Essay 2: Retailer Reputation in a Distribution Channel investigates the consumer’s passive acquisition of information. Specifically, I am interested in the interplay between the consumer’s price-quality inference and vertical coordination between the manufacturer and the retailer. Ample empirical evidence supports that consumers infer unobserved product qualities from observed prices (e.g., Tellis and Wernerfelt 1987) and seller reputation (e.g., Purohit and Srivastava 2001). However, the prices themselves depend on the vertical supply structure. I develop a model of signals issued by firms in a vertically separated (decentralized) channel. Specifically, a manufacturer sells through a retailer with a limited reputation where consumers use the observed retail price to infer product quality. I find that the signaling role of the retail price can facilitate channel coordination. Furthermore, this effect is moderated by the retailer’s reputation. Surprisingly, the manufacturer, the retailer, and consumers can all become better off when the retailer is less reputable

Impact Of Advertising Content On Food Demand By Overweight And Normal-Weight Individuals

This study compares the food demand shift and rotation effects of anti-obesity and healthy food advertising on both overweight and normal-weight individuals. We show that consumer differentiation by weight is crucial in fully understanding the effects of advertising content on food demand. Our results suggest that anti-obesity advertising is more effective for overweight subjects and healthy food advertising is more effective for normal-weight subjects. We discuss possible explanations consistent with the empirical results and provide important information for policy-makers necessary to design and implement the most effective advertising campaigns for encouraging people to eat healthier foods

Effects of Nano-Carbon Water-Retaining Fertilizer on Yield and Nitrogen and Phosphorus Utilization Efficiency of Tuber Mustard

The effects of nano-carbon water-retaining fertilizer on yield, quality of tuber mustard, and fertilizer utilization efficiency were studied with the field experiments compared to the local tuber mustard fertilizer with equal amount of effective composition. The results showed that the yield of tuber mustard was 50 670—56 496 kg/ha in treatments of nano-carbon water-retaining fertilizer decreasing by 10%—40%, and compared with local tuber mustard fertilizer, the average yield was increased by 94.8%. The yield increasing rate of tuber mustard was 93.0% in treatment of nano-carbon water-retaining fertilizer decreasing by 30%. The average fertilizer utilization efficiency of nitrogen and phosphorus was 54% and 39.7%, respectively, the average increment of fertilizer utilization efficiency was 36% and 37%, respectively compared with local tuber mustard fertilizer. Especially in treatment of reducing nano-carbon water-retaining fertilizer by 30%, the nitrogen and phosphorus fertilizer utilization efficiency was increased by 64% and 56%, respectively. By comprehensive comparison, it was found that nano-carbon water-retaining fertilizer and the treatment of 30% reduction could significantly improve the yield of tuber mustard and fertilizer utilization efficiency, and have popularization and application value in the Three Gorges Reservoir area

Improved multi-strategy artificial rabbits optimization for solving global optimization problems

Abstract Artificial rabbits optimization (ARO) is a metaheuristic algorithm based on the survival strategy of rabbits proposed in 2022. ARO has favorable optimization performance, but it still has some shortcomings, such as weak exploitation capacity, easy to fall into local optima, and serious decline of population diversity at the later stage. In order to solve these problems, we propose an improved multi-strategy artificial rabbits optimization, called IMARO, based on ARO algorithm. In this paper, a roulette fitness distance balanced hiding strategy is proposed so that rabbits can find better locations to hide more reasonably. Meanwhile, in order to improve the deficiency of ARO which is easy to fall into local optimum, an improved non-monopoly search strategy based on Gaussian and Cauchy operators is designed to improve the ability of the algorithm to obtain the global optimal solution. Finally, a covariance restart strategy is designed to improve population diversity when the exploitation is stagnant and to improve the convergence accuracy and convergence speed of ARO. The performance of IMARO is verified by comparing original ARO algorithm with six basic algorithms and seven improved algorithms. The results of CEC2014, CEC2017, CEC2022 show that IMARO has a good exploitation and exploration ability and can effectively get rid of local optimum. Moreover, IMARO produces optimal results on six real-world engineering problems, further demonstrating its efficiency in solving real-world optimization challenges

An Improved Multi-Strategy Crayfish Optimization Algorithm for Solving Numerical Optimization Problems

The crayfish optimization algorithm (COA), proposed in 2023, is a metaheuristic optimization algorithm that is based on crayfish’s summer escape behavior, competitive behavior, and foraging behavior. COA has a good optimization performance, but it still suffers from the problems of slow convergence speed and sensitivity to the local optimum. To solve these problems, an improved multi-strategy crayfish optimization algorithm for solving numerical optimization problems, called IMCOA, is proposed to address the shortcomings of the original crayfish optimization algorithm for each behavioral strategy. Aiming at the imbalance between local exploitation and global exploration in the summer heat avoidance and competition phases, this paper proposes a cave candidacy strategy and a fitness–distance balanced competition strategy, respectively, so that these two behaviors can better coordinate the global and local optimization capabilities and escape from falling into the local optimum prematurely. The directly foraging formula is modified during the foraging phase. The food covariance learning strategy is utilized to enhance the population diversity and improve the convergence accuracy and convergence speed. Finally, the introduction of an optimal non-monopoly search strategy to perturb the optimal solution for updates improves the algorithm’s ability to obtain a global best solution. We evaluated the effectiveness of IMCOA using the CEC2017 and CEC2022 test suites and compared it with eight algorithms. Experiments were conducted using different dimensions of CEC2017 and CEC2022 by performing numerical analyses, convergence analyses, stability analyses, Wilcoxon rank–sum tests and Friedman tests. Experiments on the CEC2017 and CEC2022 test suites show that IMCOA can strike a good balance between exploration and exploitation and outperforms the traditional COA and other optimization algorithms in terms of its convergence speed, optimization accuracy, and ability to avoid premature convergence. Statistical analysis shows that there is a significant difference between the performance of the IMCOA algorithm and other algorithms. Additionally, three engineering design optimization problems confirm the practicality of IMCOA and its potential to solve real-world problems