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The crisis between handling the COVID-19 pandemic and natural disasters has been a significant threat worldwide, especially for developing countries like Indonesia. The activities of the humanitarian aid supply chain when a natural disaster occurs, especially during the COVID-19 pandemic, have several unmanaged risks. This study specifically identifies risks that occur in the supply chain of humanitarian aid for disaster victims from Humanitarian NGOs in Aceh province. This study uses case-study-based research with mixed methods, where quantitative analysis is used to analyze prioritized risks, and qualitative research is used to create the framework of recovery strategies. The identification of possible risks is made using literature review, several news articles evaluation, and discussions with experts. The results show that there are 35 risk events and 30 risk agents identified in the humanitarian aid supply
chain for disaster victims in Aceh during COVID-19 Pandemic. From the Pareto diagram, there are three risk agents identified with the highest Aggregated Potential Risk (APR) value. They are Natural
Conditions, Health, and Changes in Department policies. The recovery strategies are built in the form of an AURA framework for a long-term perspective's solution. These recovery strategies are expected
to be used not only for COVID-19 threats but also for other long-term disruptions or crises that might
occur in the future.
As a result of Industry 4.0, the creation of new technology solutions, and the usage of the Internet in business systems, the concept of logistics 4.0 was developed. This thesis aims to highlight contemporary trends in logistics, the innovativeness of logistics, and new visions of the idea of Logistics 4.0. This approach's fundamental elements are automatic identification, real-time localization, automatic data collecting, networking and integration, data processing and analysis, and commercial services. The following would be a few of the Logistics 4.0 technologies highlighted in the study and are described in detail: Cloud computing, blockchain, big data, robotics, and automation, augmented reality, drones, 3D printing, and autonomous guided vehicles are some of the terms used by the logistics industries and the business or digital business models being implemented with the age of digitalization.
The Alfajor is an Argentine delicacy that shows no limits in its development in the country and abroad. Over the last 140 years, it has managed to conquer the palates of Argentines, Paraguayans, Uruguayans and Chileans as a sweet snack or dessert. Because of this outstanding development, the product captured the interest of Brazilian tourists, who incepted the Alfajor in this vast South-American country. Nowadays, several local and imported Alfajores are commercialised
through this new market. Still, many Brazilians have not heard of the product yet, and there are further challenges that Alfajor companies must overcome in their internationalisation process. This work explores these challenges based on the Uppsala Model, explaining how an intermediary can help overcome the Liability of Outsidership. Moreover, an Alfajor’s Psychic Distance Scale is elaborated to
measure the Liability of Foreignness and how the Food Culture Distance with Brazil can harden the introduction of this product in an unfamiliar market.
Earnings management is considered as a strategy applied by managers of a firm to intentionally modify the financial information to deceive stakeholders and achieve economic and contractual benefits. One of the forms of earnings management is accruals-based earnings management that occurs from accounting choices, adjustments, and managerial decisions. The primary objective of this thesis project is to investigate the impact of accrual-based earnings management on firms’ financial performance. A sample of 14 firms is selected from German automobile manufacturing firms listed on the Frankfurt Stock Exchange (FSE) over the period from 2010 to 2019 using a purposive sampling technique. Data is gathered from financial reports of sample firms. This study measured accrual-based earnings management through discretionary accrual (DA) using the modified Jones model, while firms’ financial performance is measured using return on assets (ROA). In the econometric model, the dependent variable is return on assets (ROA), whereas the independent variable is discretionary accruals (DA) that incorporate with other three control variables such as firm size (SIZE), leverage (LEV), and liquidity (LIQ). This analysis is done using a panel data regression model to assess the relationship between variables. The findings show that automobile manufacturing firms listed on Frankfurt Stock Exchange are involved in income-decreasing discretionary accruals, and its impact on firms’ financial performance (ROA) is significantly positive. Furthermore, the finding of this study confirms that there is not only discretionary accruals but also size, which influences firms' financial performance. However, leverage and liquidity have an insignificant relationship with firms’ financial performance. Finally, the finding of this study may be useful for investors, financial analysts, and other interested parties to understand how firms’ earnings are manipulated and how its impact on firms' financial performance so that they can make their financial decisions and analysis accordingly.
The work performed by controllers changes over time, and due to technological evolution. Consequently, the controller competencies and academic formation to work change too. Therefore, this research aim was to answer: What is the required level of preparation of accounting and controlling graduates to handle the controller's role and tasks? To answer this question was realized an empiric research, where 32 graduates answered a survey, and it was collected 359 job advertisements. The job advertisement was analyzed using data mining applying phyton, and it was used descriptive statistics for the survey, both data set were compared using data visualization. The result demonstrated that a controller requires a set of controlling, interdisciplinary, methodological, socio-personal, and digital competencies. Obtaining these competencies are through business administration study or vocational training in business. digital competencies are not yet in demand by employer, except for business intelligence. The graduates do not master digital competencies. These findings can serve as a basis for the improvement of the curricula on which the controller training process is based.
Im Jahr 2015 einigten sich alle Mitglieder der Vereinten Nationen auf die Umsetzung der 17 Nachhaltigkeitsziele (Sustainable Development Goals - SDGs) im Rahmen der Agenda 2030, um eine weltweite Nachhaltige Entwicklung zu unterstützen. Betrachtet man die beiden Handlungsziele „Kein Hunger“ und „Nachhaltige Städten und Gemeinden“ im Kontext, werden die gegenseitigen Abhängigkeiten deutlich. Im Jahr 2050 wird erwartet, dass weltweit 66 – 75 % der Menschen den urbanen Raum bevölkern. Im Handlungsziel 2 der SDGs „Kein Hunger“ werden die globalen Unterziele wie u.a. die Sicherstellung der nachhaltigen Entwicklung der Ernährungssysteme oder die Unterstützung für kleine landwirtschaftliche Betriebe adressiert.
Addressing Systemic Risk in Europe during Covid-19: policies, limitations, and challenges ahead
(2021)
This work examines the impacts which the Covid-19 pandemic brought to the stability of the European financial sector. Lockdowns, businesses unable to operate and uncertainty about how the pandemic would evolve fueled a sharp recession. From the lessons learned in the global financial crises and the Eurozone debt crises, there’s an increasing role of macroprudential policies, especially the regiments of the Basel III framework and the monetary policy toolkit. Alongside macroprudential regulation, the European Central Bank provided substantial monetary policy easing, for instance the release of capital buffers and other capital requirements, expanding the TLTRO III and Pandemic Emergency Program which facilitated monetary policy transmission. Authorities also deployed strong fiscal policies which encompassed from tax holidays to direct transfers to households and firms. The combination of fiscal, monetary, and regulatory policy was unprecedented and helped the economy during the shutdown moments. As a result, indicators of systemic risks in the banking sector during the pandemic remained relatively stable. Nevertheless, some challenges might emerge in the medium-term when policies are phased-out, namely the increasing size of non-performing loans and the sovereign doom-loop. Thus, in the final part of this text a stress test is conducted to evaluate the possible future impacts of the pandemic in the banking sector.
The following thesis aims to explore the particular changes that occurred in user behavior on social media (Instagram, YouTube, Facebook) during the pandemic from March 2020 to present time, how these changes relate to user engagement rate and what impact these changes have on the online radio show industry from a perspective of emerging independent radio show series “Widows Radio”. For limitation purposes of the research, purposive sampling method is used to identify particular behaviors. As a result of the research, a list of changes of user behavior are identified, specific impact of these changes on user engagement rate is shown. On the base of the conducted research, several recommendations for the online radio company “Widows Radio” regarding their social media strategy are provided.
In the contemporary era, large number of companies publish their business performance as a report on the Internet. To make them usable in larger numbers, these reports must be read and labeled. This is inefficient and expensive. This study supports this business need by automatically classifying four different categories of metadata of financial reports. For training of the used random forest classifier, an active and a passive learning strategy are contrasted. The results show a clear advantage of active learning for classifying whether a financial report contains consolidated enterprise data or not. For more complicated multi-class classifications, no advantage is shown so far under the applied active learning strategy, however, there is potential to develop an alternative more efficient strategy.
Purpose: This study aims at investigating how nonprofit organisations can successfully and sustainably implement web analytics. It develops a framework based on existing literature as well as expert interviews and tests its applicability and practicability in a hands-on case study with the German nonprofit organisation Gemeinsam TECHO e.V..
Methodology: The research questions are explored through a qualitative approach via a literature review and semi-structured interviews. The author draws a convenience sample of seven German nonprofit organisations. The interviews are analysed through qualitative content analysis. Based on the results a first web analytics framework is developed which is then tested and reviewed in a practical application.
Findings: The outcome of the study is a framework with a general step-by-step plan for NPOs on how they can implement web analytics into their business.
Research limitations: The convenience sample as well as the focus on German nonprofit organisations are possible limitations. The framework should be further tested with nonprofit organisations in different settings and conditions: country, industry, etc. Another limitation is that during the practical application only a single pass of the framework was done. Additional testing of the framework with several iterations might uncover more suggestions for improvement.
Value: This paper seeks to propose guidelines that give valuable hints for nonprofit organisations looking to implement web analytics into their business. Some existing web analytics frameworks can be found in current scientific literature; however, little empirical evidence exists for the case of nonprofit organisations. This study provides a new viewpoint on the use of web analytics which may be of use for those working in the context of nonprofit organisations.
Keywords: web analytics, nonprofit organisations, NPOs, TECHO, marketing, data analytics, web analytics framework
Green consumerism plays a crucial role in tackling environmental issues. This research aims to understand the different factors that determine the green purchase intention of China’s and Germany’s Generation Y by using an extended version of the Theory of Planned Behavior model. The empirical research builds on a questionnaire with a sample size of 330 Chinese and 275 German millennials. The results of the multiple linear regression analysis indicate that environmental concern, subjective norm, and perceived consumer effectiveness are significant predictors of green purchase intention for both millennial groups. Besides, the analysis highlights that subjective norm has the strongest influence on Chinese millennials’ green purchase intention, while environmental concern appears to be the top predictor for German millennials. In contrast, the perceived availability of green products fails to show a significant relationship with green purchase intention for either group. The variables perceived quality of green products for German millennials and trust in eco-labels for Chinese millennials also show no significant relationship with green purchase intention. These cross-group differences can be linked to cultural differences. Therefore, the results of this study contribute to a better understanding of the green purchase behavior of both millennial groups and provide useful insights for policymakers and marketers to improve their strategies.
This research has collected the story branding content published by Volkswagen on its YouTube and Tencent Video's official platform from 2018 to 2019. A total of 12 samples. Explore how successful multinational companies can build their brand identity and communicate with local consumers through storytelling. What changes did Volkswagen make for localization? What core values does it retain? A content analysis of video content is conducted, which combines narrative analysis and cognitive science. This study integrates the story elements proposed by Vincent, Foss, Fog, et al. and analyzes the narratives in settings, characters, objects, events, and messages. Supplemented with the cognitive science variables proposed by Simon (2016) for discussion. This study found that in the content on Tencent Video, Volkswagen used a China-specific connection between the country and people to deliver brand knowledge. The stories on YouTube are more concerned with the relationship between individuals and cars. However, the final message to be delivered is not much different. Volkswagen has packed the automotive products into the message of love and trust. They both put stress on people’s feelings toward cars but not the performance and value of the car itself.
We are living in the age of data, organizations are facing exponential growth in data. This growth
of data if not dealt with in the right approach will do more harm than good to the organization.
One of the most important aspects of data is data quality. Increased data quality ensures better
decision-making, thereby enabling companies to stay competitive in the market. Data quality
directly affects business decision-making, consequently having a direct effect on the KPIs of the
organization. So it is integral for growing organizations to gain an understanding of where they
stand with regards to their data quality to make improvements needed so data quality problems
won’t affect the organization's goals and KPIs. The topic of data quality is a topic that has been
addressed in numerous researches and from different aspects, there are many established and
interesting studies that have been done and resulted in different frameworks that are followed in
our days now and that shows how rich and important this topic is. The thesis aims to gain a more
precise understanding of how data quality can affect the ability of an organization to achieve the
set key performance indicators (KPIs). To do that this study will take a live example which is the
company of Uberall and do a case study on it, the situation of data quality of Uberall was
analyzed through interviews with different employees from different departments. This research
gives an insight into some precise data quality problems that Uberall is currently facing and
needs to address .
This thesis proposes a framework for extracting crucial textual information from the U.S. Securities and Exchange Commission annual 10-K reports using multiple natural language processing techniques. Ongoing progress has been made on retrieving the summary or sentiment from financial text in recent years due to the large volume of data and advanced computing power. However, the combination of different techniques for generating insight from 10-K textual content has not yet been addressed in the literature. Therefore, the main study contribution is designing a framework that integrates text summarization, sentiment analysis, topic modeling, and regression to provide readers with several indicators to help them acknowledge the valuable information in 10-K reports more efficiently and effectively. The framework considers various models but focuses on transformer-based models because the literature review indicates that these models surpass the performance of others on most natural language processing tasks. As a result, the framework successfully condenses the report content by 88% into the most critical sentences with the sentiment and discussed topic. Finally, these extracted features are further used to predict future company growth that, in addition to the traditional quantitative metrics, can be a new reference for investors in making more comprehensive decisions.
In this study two emerging markets and two developed financial markets are
examined for herd behaviour using a market-wide approach. The emerging market
representatives are Turkey and India whereas the developed market representatives
are Italy and Germany. The model developed by Chang et al. (2000) is used to
detect herd behaviour in the respective markets from January 2008 to September
2020. The four markets of interests are tested for the presence of herding under
different market conditions.
Evidence of market-wide herding is found at the Indian market when examining the
whole sample period. No evidence of market-wide herding for the whole sample
period is detected for Turkey, Italy and Germany. The sample has been separated
into falling and rising market days to detect potential asymmetry of herding
behaviour. Only the Indian market displayed evidence of herding during bullish
market days. Turkey, Italy and Germany showed no evidence of herding neither
during bullish nor bearish market days. Lastly, the sample was split according to
extreme market movements, using the 1% criteria. Evidence suggests that during
extreme market movements the Italian market shows herding patters. However, this
does not apply to Turkey, India and Germany.
Abstract
A competitive design of a supply chain is achieved by considering all the variables that affect the entire system and their interaction in the decision-making process. In developing countries, where the supply chains are usually labour intensive and where institutional and infrastructural conditions for competitive supply chains are still setting, players should give importance to the strategy of joint forces to become stronger in national and international markets.
This research presents a framework for designing agricultural supply chains in developing countries based on simulation software and describing a collaborative model that supports joint investments, information exchange and coordination. The framework is tested using an illustrative case of a developing country agricultural supply chain. This case is analysed throughout the research to demonstrate how the proposed strategy may aid in the attempt to open possibilities for small actors to play in the competitive international marketplace.
The strategy comprises four components derived from the consulted literature and the multi- method simulation tool for supply chain optimisation anyLogistix. First, Greenfield Analysis to find the best location for processing facilities to consolidate and prepare the product for the shipment. Then, Simulation and Comparison experiments to analyse the solutions' behaviour and identify which one is the most suitable and advantageous in this partnership, aiming for the best profit and adequate lead times. Finally, a Sensitivity analysis to evaluate how changes in the main variables affect the selected configuration's performance and make informed decisions knowing the associated variability of the outcomes.
Keywords: Supply Chain; Agricultural Supply Chain; Supply Chain design; Collaboration in Supply Chains; Agricultural Supply Chain in developing countries.
Die Bearbeitung dieser Masterarbeit konzentriert sich auf die genaue Ausarbeitung des neuen Regierungsentwurfs zum FüPoG II im Hinblick auf die Einführung einer verbindlichen Frauenquote für deutsche Vorstände. Dabei soll die Fragestellung untersucht werden, inwieweit die Umsetzung einer solchen Quote unter Beachtung juristischer Regulatorien möglich ist. Insbesondere soll hierfür die verfassungsrechtliche Zulässigkeit der Vorstandsquote unter dem Aspekt der Vereinbarkeit mit Art. 12 Abs. 1 und Art. 14 Abs. 1 GG geprüft und kritisch beurteilt werden. Damit zusammenhängend stellt sich als Unterfrage, ob eine fixe Quote für Vorstände ebenso gut durchsetzbar ist wie die bereits eingeführte Geschlechterquote in Aufsichtsräten börsennotierter und mitbestimmungspflichtiger Unternehmen.
The study of disruptions management and resilience connected to the current COVID-19
outbreak has become an essential field in supply chain management. Post-disruption recovery
analysis amid the pandemic outbreak is relevant for organizations to respond to disruptions and
create new growth opportunities. Therefore, the performance impact of COVID-19 in the
German food retail supply chain is investigated using a hybrid case-study and discrete-event
simulation model implemented in anyLogistix software. Potential improvements and supply
chain actions are provided in response to the identified challenges. Moreover, a framework with
strong recommendations for stabilization and recovery in a post-disruption environment is
created as a guideline for the main supply chain actors in the food retail business.
Fintech is an innovative tool that applies technology to improve financial services.
Mobile Baking is the most common product of Fintech and has vast prospects to
improve access to financial resources for the previously unbanked populations. The role
of Fintech in providing inclusion is especially vital in developing countries- where the
proportion of the financially excluded remains high. This study focuses on the role of
M-Banking in serving mentioned populations, and identifies the factors influencing
adoption and usage of Fintech services. The last part also introduces the case of
Azerbaijan-a former USSR country, and concludes by drawing the potential paths of its
Fintech-inclusion development.
The purpose of this study is to investigate marketing-mix strategies (adaptation and standardization) for the entry of Western footwear companies into the Chinese footwear market by exploring differences among Chinese consumers and differences in buying behavior for casual shoes and formal shoes in the Chinese footwear market. Three research gaps were identified and developed into research questions based on the analysis of extensive literature.
Consumer data was collected through questionnaire surveys conducted in China. The results of this research suggest a standardized product strategy and that price, place, and promotion strategies are adapted to meet Chinese consumers’ unique needs for buying footwear products.
The results also indicated that consumers from diverse backgrounds consider different factors when buying casual and formal shoes and considered how they influence the marketing mix strategy. In conclusion, and based on the study’s results, the paper considers the implications for management to provide recommendations for businesses interested in the Chinese footwear market.