Creating Brand Image Profile by Social Media Analysis

The purpose of creating a brand image profile is to measure the brand perception of consumers considering brand attributes. Thus, marketing decisions can be made based on the brand's strengths and weaknesses by determining them. The brand image profile is traditionally created using the attitude scales and surveys. However, alternative methods are needed since the questionnaires' responses are careless, the number of participants is relatively low and the cost per participant is high. In this study, as an alternative method, creating a brand image profile by analyzing social media data with artificial intelligence was made for the iPhone product. Firstly, the focus group study determined the attributes related to the last version of the iPhone. Then, between December 17th, 2019 and March 23rd, 2020, 87.227 tweets that include these attributes in English were collected from the Twitter social media platform through the RapidMiner data mining tool. Sentiment analysis was performed on collected tweets by the MeaningCloud text mining tool. In this analysis, positive and negative emotions were tried to be detected through artificial intelligence algorithms. Net Brand Reputation Score (NBR) was calculated using the positive and negative tweets amount for each attribute separately. Brand image profile was created by skew analysis using NBR values. As a result, it is thought that social media analysis can be a complementary method that can be used with traditional methods in creating a brand image profile. So, it is seen as an inevitable method to use in further studies to make sentiment analysis by processing raw data received from the Social Media platforms through artificial intelligence algorithms to transform the product label or the perspectives of an event into meaningful information.

Financial Instrument Forecast with Artificial Intelligence

In ancient times, trade was carried out by barter. With the use of money and similar means, the concept of financial instruments emerged. Financial instruments are tools and documents used in the economy. Financial instruments can be foreign exchange rates, securities, crypto currency, index and funds. There are many methods used in financial instrument forecast. These methods include technical analysis methods, basic analysis methods, forecasts carried out using variables and formulas, time-series algorithms and artificial intelligence algorithms. Within the scope of this study, the importance of the use of artificial intelligence algorithms in the financial instrument forecast is studied. Since financial instruments are used as a means of investment and trade by all sections of the society, namely individuals, families, institutions, and states, it is highly important to know about their future. Financial instrument forecast can bring about profitability such as increased income welfare, more economical adjustment of maturities, creation of large finances, minimization of risks, spreading of ownership to the grassroots, and more balanced income distribution. Within the scope of this study, financial instrument forecast is carried out by applying a new methods of Long Short Term Memory (LSTM), Recurrent Neural Network (RNN), Convolutional Neural Network (CNN), Autoregressive Integrated Moving Average (ARIMA) algorithms and Ensemble Classification Boosting Method. Financial instrument forecast is carried out by creating a network compromising LSTM and RNN algorithm, an LSTM layer, and an RNN output layer. With the ensemble classification boosting method, a new method that gives a more successful result compared to the other algorithm forecast results was applied. At the conclusion of the study, alternative algorithm forecast results were competed against each other and the algorithm that gave the most successful forecast was suggested. The success rate of the forecast results was increased by comparing the results with different time intervals and training data sets. Furthermore, a new method was developed using the ensemble classification boosting method, and this method yielded a more successful result than the most successful algorithm result.

The Effects of Internal Audit, Audit Committee and Firm Characteristics on Audit Fees in a Multi-Country and Industry Setting

This paper examines the association between audit fees and attributes of internal audit (IA), audit committee (AC), as measured by independence and financial expertise, as well as characteristics of the firm. The determinants of audit fees have been extensively investigated in the prior literature, but the results are conflicting. We develop a comprehensive model from a multi-country and multi-industry perspective. A total of 3,136 companies covering a period of 10 years (2011-2020) with 15,247 observations from 55 countries were included in this study. We found that the most critical variables that have a significant positive effect on the audit fees are client size, leverage (risk), profitability, complexity, losses, AC independence, AC expertise and auditor size. The study also shows that audit pricing is significantly negatively related to foreign operations, auditor tenure, and internal audit independence. The results highlight variables that affect audit fees across a range of countries/industries.

Measurement of Employees on Human Resources with Fuzzy Logic

Artificial intelligence, which is the indispensable technology of our age, has started to gain a place in many institutions. Institutions give great importance to human resources management because hiring the right employee for the job will increase productivity within the organization. When recruiting personnel for the position, human resources face difficulties such as measuring the success levels of applicants and deciding whether they are suitable. In this study, in order to provide solutions to the difficulties encountered, a decision-making mechanism is created by using the fuzzy logic method, which is one of the artificial intelligence techniques. This decision-making mechanism measures the performance of people applying for recruitment. While measuring performance, all applications are taken into consideration, and a rule base is formed according to graduation status and experience. The system, which is based on this rule base, evaluates people according to the inputs and finds out their success levels in return. According to the results, it is decided whether the persons are suitable for the position sought. When human resources departments in corporations are combined with artificial intelligence technologies, an advantage will be achieved in the competitive environment between corporations.

Knowledge Management and Competitive Advantage of Listed Consumer Goods Manufacturing Companies in Nigeria

The study investigated the effect of knowledge management on the competitive advantage of Nigerian consumer goods businesses. A survey research design was used for the study. The management staff of six major consumer goods firms were included in the study’s population: Flour Mills Nigeria Plc., Cadbury Nigeria Plc., Guinness Nigeria Plc., Nestle Nigeria Plc., Honeywell Flour Mills and PZ Cussons Nigeria from which a sample of 384 was drawn using power analysis. A structured questionnaire was used to collect information from the respondents. The data collected were analyzed using descriptive statistics of frequency counts and simple percentages. In addition, covariance-based structural equation modelling (CB-SEM) was used to achieve the study’s objectives. The findings from the study revealed that knowledge acquisition (β = 0.541; p = 0.001), knowledge sharing (β = 0.672; p = 0.001), knowledge creation (β = 0.774; p = 0.001), knowledge codification (β = 0.450; p = 0.001) and knowledge retention (β = 0.853; p = 0.001) had a significant positive effect on consumer goods company’s competitive advantage. The study concluded that knowledge management played an important role in enhancing competitive advantage when adequately managed. It was recommended that the authorities in charge of the consumer goods companies ensure management staff quickly get any information needed within their working environment and ensure a horizontal information flow. In addition, the management should constantly develop new knowledge and ideas as well as providing appropriate communication and information technology (IT) gadgets to boost competitive advantage.

Does Brand Love Last Forever? : A Study on Turkey’s Lovemarks

Brand love has become an important concept in both the academic and business worlds. There are some studies in the literature conducted on consumers regarding the brand love, but no study focuses on brands that consumers are in love with. Therefore, to analyze how brand love is created and to identify the components of a sustainable brand love, we conducted a qualitative study on the brands that achieved the lovemark status several times in the survey conducted on the consumers in Turkey. We used the categories in the 2019 lovemark survey, a study conducted by Ipsos for MediaCat magazine every year, as the basis, and we evaluated brands that have been selected as lovemarks in their respective categories at least five times. Our study concluded that the brands created brand love through quality in product or service as well as diversity, customer satisfaction, brand trust, innovative products, sincerity, and emotional intimacy, being a solution-oriented brand, as demonstrated in other studies in the literature, and in addition, by creating social responsibility projects, and being accessible. These brands also made brand love sustainable through reliability, service, relevance, stand behind the promise, innovation, brand image, customer satisfaction, a sense of community, customer experience, emotional bond, trust, people-oriented communication strategy, real-life compatible products and services as well as creation of different experiences.

The Impact of Liquidity Risk Management on the Financial Performance of Saudi Arabian Banks

This paper aims to analyze the impact of liquidity risk management on the financial performance of selected conventional banks in Saudi Arabia for the period of 2002-2019. Liquidity risk is measured with the loan to deposit ratio (LTD) and cash to deposit ratio (CTD). Financial performance is measured by the Return on Equity (ROE). Equity to total asset ratio (ETA) is used as the control variable. The study uses the panel data method (Pool, Fixed-effects and Random-effects) for testing the study hypothesis. The results show that liquidity risk has a significant negative impact on the financial performance measured by Saudi Arabian banks.

Country-Level Size Effects in International Asset Pricing

This paper investigates whether small markets offer higher risk-adjusted expected returns using a large set of developed and emerging markets over a time span of up to four decades. The results show that expected returns are significantly lower in larger markets, an effect more pronounced in emerging rather than developed countries. The relationship between size effects and the level of market segmentation in emerging countries is further explored in the context of financial market integration. The size premium is strong and persistent over time independently of the (fading) segmentation premium documented in the literature. Markets size effects remain statistically and economically significant in the presence of various control factors and account for up to 1% per year in terms of expected returns in emerging countries.

Auditing Techniques to Minimize Accounting Related Fraud and Errors: A Qualitative Analysis with the Interview Method

Accounting is more integrated with the technology today compared to the previous years. The increase in a variety of technological developments and commercial transactions has further increased the number and type of errors as well as frauds related to the accounting profession. This causes misleading information for several stakeholders. Stakeholdes sometimes make false decisions based on the financial statements created as a result of false and fraudulent transactions. In order to minimize the errors and frauds concerning the accounting system of enterprises, effective internal controls and auditing systems should be in order. It is evident that, setting up the required internal controls and auditing systems reduce asset losses and provide great benefits in the long run for firms. Existence of strong internal controls and auditing systems in enterprises has gained great importance in Turkey. This study provides information about the audit techniques that can minimize accounting related frauds and errors in businesses. The research includes and employs an interview with auditing professionals as the research methodology. Auditors working within three audit firms were selected by simple random sampling via the LinkedIn social media. The three participants were directed 10 semi- structured and open-ended questions. Qualitative analysis was adopted for this study. According to the results of research, companies use a number of tools to prevent accounting related frauds and errors. These most effective tools to minimize the frauds and errors are detected as internal auditing, internal controls and independent (external) auditing. Auditing professionals have high awareness about accounting related fraud and errors. But, auditor independency should be higher, proactive approach must be utilized and auditors must closely follow the new laws and regulations in addition to being familiar with the firms’s operations and sectors to minimize the fraud and errors. The Benford's law, artificial neural networks, analytical methods, data mining, red flags and analytical methods are commonly used by the auditors against frauds and errors. In general, the internal controls and auditing professions are in a much better situation today in Turkey compared to the previous years. But, this is still not adequate and there is a long way to complete ahead based on the opinions of auditing professionals.

Hosting Major International Sports Events in a Country: A Socioeconomic Impact

This research focuses on the impact of sponsoring major sports events concerned with the socioeconomic aspects of Qatar. Context is the hosting of FIFA 2022 in Qatar. A questionnaire has been developed based on the underpinning theory, which included seven dimensions of measuring socioeconomic impact that covered Micro, Meso, Macroeconomic, Employment, Quality of Life, Social Cohesion and Environmental aspects. Questionnaire survey was conducted for a sample size of 126, which included the managers from tourism industry and sponsoring of sports events. The research methodology involved descriptive statistics calculations using MS Excel and SPSS. The response score was collected on a 5-point Likert scale for quantitative measures and the Mean, Standard Deviation, Kurtosis, Skewness and Frequency Distributions were computed for seven dimensions. The responses were later categorized into degrees of agreement with a priori scale to understand the relative impact of sponsoring sports events concerned with socioeconomic aspects. The results have indicated that, the highest impact would be on the creation of Environmental Consciousness among the citizens of Qatar followed by the impact on the Micro, Meso and Macroeconomic aspects of the country. These revelations have led providing suggestions to policy makers, which would be useful particularly in the present situation where Qatar is planning for FIFA 2022.