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  • Berlin  (48)
  • Berlin International  (48)
  • Charité
  • Polnisches Institut
  • SB Lübben
  • Berlin International University of Applied Sciences. Faculty of Business Administration  (48)
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  • Berlin  (48)
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  • Berlin International  (48)
  • Charité
  • Polnisches Institut
  • SB Lübben
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  • 1
    UID:
    kobvindex_INT60853
    Format: 39 pages : , illustrations ; , 21 × 29.7 cm.
    Content: AI-GENERATED ABSTRACT: Abstract: "There are decades where nothing happens; and there are weeks where decades happen", (Lenin, date of publication not identified), and how can a country tailor its marketing strategies around multiple crises is a question to be asked. The research will offer an in-depth examination of various spheres of interest, focusing on three digital media campaigns within the context of Turkey as a touristic destination. Amadeus IT Group's data will be utilized for the study, and statistical analysis will be conducted to investigate the effectiveness and the impact of these campaigns on the traveller's decision-making process. Unexpected findings will shift the existing paradigm, leading to a second round of investigation to further understand these results. Upon the potential event of failing to report positive results, a set of conclusions will be drawn, and these findings will subsequently lead to various recommendations, which form the core emphasis of this study. This research intends to contribute to the body of knowledge by providing insights into how a country's marketing strategies can be adapted, and moreover, and how a country should evaluate itself before demanding media services. In the realm of digital marketing, the study can help marketers understand how to better tailor their strategies to suit different types of customers, but moreover the existing need for exploration with a focus on campaign metrics. Keywords: crisis marketing, digital media campaigns, Turkey, tourism, Amadeus IT Group, statistical analysis, decision-making, digital marketing strategies, campaign metrics, media services evaluation
    Note: DISSERTATION NOTE: Bachelor of Arts thesis in International Management and Marketing, Berlin International University of Applied Sciences, 2023. , MACHINE-GENERATED CONTENTS NOTE: Table of Contents 1. Introduction...........................................................2 1.1 Research Problem..................................................2 1.2 Research Objectives................................................2 1.3 Research Questions................................................2 1.4 Scope and Limitations..............................................2 1.5 Significance of the Study..........................................2 2. Literature Review.....................................................3 2.1 Literature Review..................................................3 2.2 Theoretical Framework.............................................3 2.3 the Consumption of Tourism........................................3 2.4 Criticism of Tourism...............................................3 2.5 Low-probability Events............................................3 2.6 Tourism in Turkey..................................................3 2.7 Persistent Events..................................................3 2.8 Amadeus and Amadeus Campaign......................................3 3. Methodology...........................................................4 3.1 Research Design....................................................4 3.2 Quantitative Techniques............................................4 3.3 Qualitative Techniques.............................................4 4. Findings..............................................................5 4.1 Correlation Analysis...............................................5 4.2 T-test Analysis....................................................5 4.3 Supporting Arguments...............................................5 5. Conclusion.............................................................6 6. References.............................................................7 7. Appendix...............................................................8 7.1 Interview..........................................................8
    Language: Undetermined
    Keywords: Academic theses
    URL: FULL
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  • 2
    UID:
    kobvindex_INT60916
    Format: 87 pages : , illustrations ; , 21 × 29.7 cm.
    Content: AI-GENERATED ABSTRACT: Abstract: This thesis aims to examine the impact of AI-enabled Customer Relationship Management (CRM) in small and medium-sized e-commerce businesses in Germany and India. The adoption of Artificial Intelligence (AI) in CRM is emerging as a solution for businesses in their marketing operations. The research addresses the competitive advantages including customer personalisation, segmentation, lead generation, targeting, data, and predictive analysis. This study gathers a mix of qualitative and quantitative approaches where survey respondents (N=30) and Interviews (N=10) include case studies of marketing professionals and executives. The research questions are analysed with two hypotheses which explains the value of AI in CRM for small and medium sized e-commerce businesses. The AI features in CRM provided by MoEngage are deeply analysed. The results show e-commerce businesses improve customer engagement and sales by effective personalisation and segmentation after implementation of AI-enabled CRM. Keywords: Artificial Intelligent (AI), CRM, AI-enabled CRM, small and medium-sized businesses, e-commerce, marketing, Segmentation, Personalisation.
    Note: DISSERTATION NOTE: Master of Business Administration thesis, Berlin International University of Applied Sciences, 2023. , MACHINE-GENERATED CONTENTS NOTE: Table of Contents abstract..........................................................................................................v 1. Introduction................................................................................................1 1.1. Hypothesis........................................................................................2 2. Literature Review......................................................................................2 2.1. Artificial Intelligence (ai).................................................................2 2.2. Ai Transforming Crm in E-commerce..............................................8 2.3. Importance of Ai-enabled Crm.......................................................11 2.4. Ai-enabled Crm Adds Value to Small and Medium E-commerce Businesses.......................................................................................12 2.5. Crm in India and Germany..............................................................14 2.6. Challenges Faced by Small and Medium-sized E-commerce Businesses......................................................................................15 2.7. Moengage.......................................................................................17 2.7.1. About Moengage........................................................................17 2.7.2. Ai-enabled Crm Moengage: Sherpa..........................................19 2.7.3. Deeper Insights on Moengage Ai Capabilities in Crm.................20 2.7.3.1. How Does it Actually Predict?..........................................21 3. Research Methodology............................................................................21 3.1. Research Design..............................................................................22 3.2. Sampling..........................................................................................22 3.2.1. Qualitative Interviews...........................................................22 3.2.2. Survey...................................................................................23 3.3. Data Collection................................................................................23 3.3.1. Qualitative Interviews...........................................................23 3.4. Survey Forms................................................................................25 3.5. Data Analysis..................................................................................25 3.5.1. Interviews Analysis...............................................................25 3.5.2. Survey Analysis.....................................................................25 3.6. Validity and Reliability.......................................................................25 3.7. Ethical Considerations.....................................................................26 4. Results......................................................................................................26 4.1. Interview Results.............................................................................26 4.2. Survey Results................................................................................31 5. Discussions...............................................................................................35 5.1. H1: Implementing Ai-enabled Crm Systems in Small and Medium-sized E-commerce Businesses Improves Customer Engagement and Personalisation............................................................................35 5.2. H2: Small and Medium-sized E-commerce Businesses That Adopt Ai-enabled Crm Systems in India and Germany Experience Improved Customer Targeting and Segmentation........................................................38 6. Limitations and Scope for Future Research.................................................39 7. Conclusion................................................................................................39 8. References...............................................................................................41 9. Appendices...............................................................................................53
    Language: Undetermined
    Keywords: Academic theses
    URL: FULL
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  • 3
    UID:
    kobvindex_INT61010
    Format: 34 pages : , illustrations ; , 21.59 × 27.94 cm.
    Content: AUTHOR-SUPPLIED ABSTRACT: Abstract: This paper is an explanation of the new technologies and cryptocurrencies such as Bitcoin and Ethereum. It gives an in-depth explanation of what blockchain is, covering its characteristics, main challenges, and criticisms. It delves into the Non-Fungible token space, explaining the main characteristics and challenges in the retail fashion industry and also analyzing a study case from Nike, Incorporated where they acquired the studio/team called RTFKT (pronounced "artifact"). It finishes the study with an analysis of the NFT industry utilizing Porter's Five Forces to understand the competitiveness of the industry and a VRIO analysis to understand if RTFKT can create a competitive advantage for Nike. Keywords: new technologies, cryptocurrencies, Bitcoin, Ethereum, blockchain, characteristics, challenges, criticisms, Non-Fungible token, retail fashion industry, study case, Nike, Incorporated, RTFKT, Porter's Five Forces, VRIO analysis, competitive advantage
    Note: DISSERTATION NOTE: Bachelor of Arts thesis in Data Science and Business, Berlin International University of Applied Sciences, 2022. , MACHINE-GENERATED CONTENTS NOTE: Table of Contents 1. Introduction 1.1. The motivation for the study 1.2 Research question 2. Methodology (Research approach) 3. Literature review 3.2 Blockchain and its essential characteristics 3.3 Blockchain and its main challenges 3.4 Proof-of-Work and Proof-of-Stake: a brief explanation 3.5 What is bitcoin, and how does it work? 3.6 What is Ethereum, and how does it work? 3.7 Non-Fungible Tokens and main characteristics 3.8 How the retail and retail luxury industry can use Non-Fungible tokens 3.9 Blockchain and Non-fungible tokens criticism and challenges 4. Nike acquiring RTFKT (Case Study) 5. Porter's five forces 5.1 Porter's Five Forces applied to the NFT industry 6. VRIO Model 7. Limitations of the study 8. Discussion 9. Results 10. Conclusion References Appendices: - Declaration Page
    Language: Undetermined
    Keywords: Academic theses
    URL: FULL
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  • 4
    UID:
    kobvindex_INT60900
    Format: 42 pages : , illustrations ; , 21 × 29.7 cm.
    Content: AI-GENERATED ABSTRACT: Abstract: Purpose: During the COVID-19 pandemic, social media platforms such as TikTok have played a significant role, drawing in content makers and performers alike. This research seeks to answer whether individuals' exposure to a song on TikTok has a different effect on their interest and degree of liking with music than exposure to the same song solely on other music streaming platforms. The research also expects to show how TikTok might be a marketing tool for musicians. Research Design and Methodology: The study uses a quantitative research approach to determine whether, or not, watching TikTok videos increases viewers' interest in and preference for a song. Quantitative information is gathered from two groups of respondents using structured surveys with PANAS questions and Likert scale questions. The research uses the reliable and accurate Music Receptivity Scale (MRS) to measure the participants' degree of liking a specific song. Findings: The results of this research examine how viewing a TikTok video effects Gen Z listeners' degree of liking a piece of new music. Participants in the baseline group were only asked to listen to a song on Spotify. The participants in the second group, who first saw a TikTok video showed more interest and liking in the song than those in the baseline group. A statistically significant difference in average scores between the two groups indicates that participants' interest and impressions of the music were affected by their exposure to TikTok. Value, originality: These results add to the expanding body of literature on TikTok as a music marketing tool, suggesting future directions for the independent music industry and general music industry. The study provides insights into the potential of TikTok as a vital tool for enhancing the degree of liking for a song, which illuminates the role of TikTok in changing music tastes and emotional reactions among Generation Z. Keywords: TikTok, degree of liking, music consumption, social media, Generation Z, music marketing, Music Receptivity Scale
    Note: DISSERTATION NOTE: Bachelor of Arts thesis in International Management and Marketing, Berlin International University of Applied Sciences, 2023. , MACHINE-GENERATED CONTENTS NOTE: Table of Contents 1. Introduction.................................................................1 2. Literature Review............................................................4 2.1. the Music Industry......................................................4 2.2. the Paradigm Shift in Unveiling Musical Talents: Accepting a New Era of Artist Discovery................................................7 2.3. Music Marketing........................................................8 2.3.1. Marketing of Emerging, Lesser-known, or Independent Artists......8 2.3.2. Overview of Tiktok as a Marketing Tool..........................10 2.3.3. Going Viral on Tiktok - Lizzo's Case............................13 2.4. Theoretical Framework on Music Marketing and Social Media.............15 2.5. Previous Research on the Impact of Tiktok on Music Consumption and Engagement..........................................................16 3. Research Design and Methodology.............................................18 3.1. Sampling Method.......................................................19 3.2. Procedure.............................................................19 3.3. Data Collection and Analysis..........................................21 4. Findings...................................................................21 4.1. Presentation of the Data..............................................22 4.2. a Comparative Analysis of Baseline Group and Tiktok Group.............25 5. Discussion................................................................28 5.1. Study Implications....................................................28 5.2. Limitations of the Study..............................................29 5.3. Future Directions.....................................................31 6. Conclusion................................................................31 7. References................................................................33
    Language: Undetermined
    Keywords: Academic theses
    URL: FULL
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  • 5
    UID:
    kobvindex_INT60918
    Format: 68 pages : , illustrations ; , 21 × 29.7 cm.
    Content: AI-GENERATED ABSTRACT: Abstract: This thesis explores the integration of business process management (BPM) and data visualization tools to optimize performance marketing campaigns. The study looks at the present status of performance marketing, the benefits of BPM in improving strategies, the importance of data visualization tools like Tableau, and the challenges and opportunities connected with their integration. The survey results show that BPM and data visualization tools are widely used in performance marketing, with moderate efficacy for BPM integration and good perceptions for data visualization. Data integration complexity, learning curves, communication and collaboration issues, implementation complexities, data accuracy and privacy concerns, time and resource constraints, and skill development in data visualization are identified through thematic analysis of interviews. Organizations may improve their performance marketing strategies and get greater results by tackling these issues and capitalizing on the advantages. This study adds to a full understanding of the integration of BPM and data visualization tools in performance marketing and gives useful insights for practitioners looking to optimize their campaigns. Keywords: Performance Marketing, Business Process Management (BPM), Data Visualization, Integration, Optimization
    Note: DISSERTATION NOTE: Master of Business Administration thesis, Berlin International University of Applied Sciences, 2023. , MACHINE-GENERATED CONTENTS NOTE: Table of Contents table of Contents.....................................................................................i list of Tables.........................................................................................ii table of Figures......................................................................................iii abstract...................................................................................................iv 1. Introduction.......................................................................................1 2. Literature Review and Theoretical Framework..........................................4 2.1. Current State of Performance Marketing and Challenges Faced...............4 2.2. Business Process Management (bpm)..................................................9 2.2.1. Importance of Business Process Management in Organizational Performance...............................................................................10 2.2.2. Role of Business Process Management.....................................11 2.3. Tableau and Its Significance in Data Visualization...............................15 2.4. Theoretical Basis for Investigating the Integration of Bpm and Tableau in Performance Marketing Strategies................................................18 3. Methodology.....................................................................................20 4. Findings............................................................................................22 4.1. Analysis of Survey Data on the Usage of Bpm and Data Visualization in Performance Marketing...................................................................22 4.1.1. Results of Survey...........................................................................24 4.2. Analysis of Interviews on the Usage of Bpm and Data Visualization in Performance Marketing.................................................................36 5. Integration of Bpm and Tableau in Performance Marketing.........................42 6. Discussion..........................................................................................51 7. Conclusion..........................................................................................53 8. References.........................................................................................56 9. Appendix...........................................................................................62
    Language: Undetermined
    Keywords: Academic theses
    URL: FULL
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  • 6
    UID:
    kobvindex_INT61049
    Format: 75 pages : , illustrations ; , 21 × 29.7 cm.
    Content: AI-GENERATED ABSTRACT: Abstract Various analyses have confirmed that the concept of "being agile" has grown considerably with increasing digitalization. During times of rapid and uncertain events like the COVID-19 pandemic, agility is an efficient methodology that helps keep a company "flexible", and, at the same time, resilient. Companies, therefore, are more prepared for possible spontaneous changes that come their way, both internally and externally. Moreover, "New Work"-the approach and concept-enables growth in organizational agility by offering flexible choices for a workforce with elements of self-organization and greater autonomy. Not every company that calls itself "agile" is alike in its approach to agility. Multiple factors, such as the techniques in individual teams or individuals, play a role. Different frameworks-like "Scrum" or "Kanban"-need to be implemented so that the company is ready to become adaptable. Furthermore, some companies appear to be "agile", but this is a myth and not really true; it is propagated simply because it is better for the companies' reputation. The aim of this research is to uncover meanings and detect the importance of agility in companies, which anticipates, in particular, flexibility, adaptability, and speed. Agility is also described as a contributor to better development and success along with increasing digitalization, even as a necessity when changes occur, viz. unexpected events like the coronavirus crisis. Advanced technology in terms of, for instance, Artificial Intelligence (AI), contributes to problem-solving and the assistance of teams. Related to this topic, "New Work" has been an important and essential development for years, but has acquired even more significance on account of the coronavirus pandemic. This is associated, among other things, with the leadership of the top management and the corporate culture, values, and work practices of the employees, and, hence, offers more "freedom" and opportunities. To provide a practical case study, the focus in the relevant section in this thesis is on the digital data-driven company ImmoScout24, an online marketplace that is run as an operating online platform. Agility in the company is thereby measured and identified with the help of self-observation, interviews, and a company survey that is distributed among all its employees. Keywords: Business agility, Digital Transformation, COVID-19, New Work, Scrum, Kanban, Project Management
    Note: DISSERTATION NOTE: Master of Business Administration thesis, Berlin International University of Applied Sciences, 2022. , MACHINE-GENERATED CONTENTS NOTE: Table of Contents Introduction................................................................................1 Main Problem Statement........................................................1 Need and Justification for the Study..........................................1 Research Aim.....................................................................2 Research Questions..............................................................2 Structure of the Thesis...........................................................3 Literature Review.........................................................................3 Definitions of Business Agility..................................................3 Business Agility-Digitalization and COVID-19..............................5 Business Agility and New Work...............................................9 Limitations of current studies...................................................10 Conceptual Framework.........................................................11 Method....................................................................................12 Results.....................................................................................13 Business Agility-General Analysis, Identification, and Evaluation....13 Business Agility-Influence of Digitalization and COVID-19...........20 Digitalization...........................................................20 COVID-19..............................................................21 Business Agility-Relationship to New Work..............................23 Business Agility at ImmoScout24............................................25 Interviews...............................................................27 Survey....................................................................30 Discussion.................................................................................35 Business Agility-Digitalization, COVID-19 and New Work.............35 ImmoScout24....................................................................38 Conclusion................................................................................42 References................................................................................45 Appendices...............................................................................54 Appendix A-Survey Questions/Statements and Results...................54 Appendix B-Domains of Business Agility................................73 Appendix C-Agile Transformation.........................................74 Appendix D-2022 Global Business Agility Survey IS24................75
    Language: Undetermined
    Keywords: Academic theses
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  • 7
    UID:
    kobvindex_INT61053
    Format: 92 pages : , illustrations ; , 21 × 29.7 cm.
    Content: AUTHOR-SUPPLIED ABSTRACT: Abstract: As a phenomenon, inflation has recently been on the rise across the globe. In the cases of some developed countries, inflation levels are reaching levels not seen in at least the previous two decades. According to Reinhart and Von Luncker (2022), across the globe, both in developing and developed countries, the world is faced with inflation above 5% on an annualized basis. By reviewing past periods of inflation throughout history, the paper intends to isolate key causes, as well as provide potential solutions and suggestions to help tackle the problem. The research will focus on both qualitative and quantitative factors that influence inflation. The quantitative part will include a time-series analysis of CPI data, interest rates, and money supply, among other variables, to find correlations that precede inflation. The qualitative part will examine geopolitical realities, psychology, and government policies. Additionally, the paper will explore the difference in perception of inflation among various economic schools and how they have influenced monetary policy. Although the paper will include examples of hyperinflation and information about inflation in the early-modern and modern periods, the main focus will be on the time period from 1960-2022, primarily pertaining to the G20 countries. The analysis will rely on data obtained from the OECD, IMF, and World Bank databases, as well as relevant central banks. The goal of the research is to provide policy makers today with useful suggestions and methods to combat inflation by identifying common trends and patterns among the analyzed examples. Two primary aspects will be considered: policy errors and external factors leading up to inflationary periods, and the responses to inflation by economic policy makers and governments, assessing their effectiveness in suppressing the phenomenon. Keywords: inflation, developed countries, causes, solutions, qualitative factors, quantitative factors, time-series analysis, CPI data, interest rates, money supply, geopolitical realities, psychology, government policies, economic schools, monetary policy, hyperinflation, G20 countries, policy makers.
    Note: DISSERTATION NOTE: Master of Business Administration thesis, Berlin International University of Applied Sciences, 2022. , MACHINE-GENERATED CONTENTS NOTE: Table of Contents Introduction .................................................................................................................. 1 Section I 1. Defining Inflation ................................................................................................. 2 2. Hyperinflations in the Modern Era ........................................................................ 9 Section II Review of Existing Literature .................................................................................. 12 Section III Methodology ......................................................................................................... 16 Results ................................................................................................................... 20 Section IV Current Reality .................................................................................................... 45 Causes of Today's Inflation ................................................................................... 46 Section V Discussion ........................................................................................................... 51 Conclusion ................................................................................................................. 55 Appendix ................................................................................................................... 56 References ................................................................................................................. 72 Figures ...................................................................................................................... 90 Table of Contents
    Language: Undetermined
    Keywords: Academic theses
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  • 8
    UID:
    kobvindex_INT60890
    Format: 32 pages : , illustrations ; , 21 × 29.7 cm.
    Content: AI-GENERATED ABSTRACT: Abstract: The COVID-19 crisis has had a profound impact on various industries worldwide, including the airline and movie sectors. Machine learning models, which play a crucial role in predicting outcomes and optimizing operations in these industries, have also been affected by the pandemic. This comparative literature review aims to explore and analyze the performance of machine learning models in the airline and movie industries during and after the COVID-19 crisis. By conducting a comprehensive analysis of relevant scholarly articles, conference papers, and industry reports, this review aims to provide insights into the challenges, adaptations, and advancements made in machine learning models pre- and post-pandemic. The relevant papers and sources were selected based on being pre- and post-pandemic. These two categories of sources were then compared for both industries to illustrate the effects of the pandemic on machine learning models in both industries, and how they have developed since this global event. The findings demonstrated that machine learning has been in use for decades in both industries. In the movie industry, the algorithms were mainly used for forecasting revenue or predicting movie success pre-pandemic, while in the airline industry, machine learning models predicted flight patterns/delays or ticket prices. While the algorithms and models in both industries struggled initially in the new dynamic environments, key differences can be synthesized between the developments since. While the airline industry continues to grow and utilizes ML as a globally demanded and necessary industry, the movie industry has still not fully recovered since COVID-19 as many consumers move to digital alternatives like streaming platforms. The findings of this review will contribute to a deeper understanding of the implications of the COVID-19 crisis on machine learning applications and provide insights for researchers, practitioners, and decision-makers in these industries. Keywords: COVID-19 Impact, Machine Learning Models, Airline Industry, Movie Industry, Predictive Analytics, Pandemic Adaptations, Comparative Analysis, Algorithm Performance, Industry Recovery, Digital Transformation.
    Note: DISSERTATION NOTE: Bachelor of Arts thesis in Digital Business and Management, Berlin International University of Applied Sciences, 2023. , MACHINE-GENERATED CONTENTS NOTE: Table of Contents Abstract..................................................................................................iii Introduction 1.1 Background and Limitations of ML in a Non-Static Environment.....................................4 1.2 Effects of COVID-19 on ML Models in the Airline and Movie Industries........................5 1.3 Academic Contribution.......................................................................................................5 Methodology 2.1 Research Design and Approach..........................................................................................6 2.2 Selection Criteria................................................................................................................6 2.3 Data Collection and Analysis.............................................................................................7 Literature Review 3.1 Machine learning in static and dynamic environments......................................................7 3.2 Types of Machine Learning: Predictive and Descriptive Learning....................................8 3.3 Machine Learning Applications in the Movie Industry: Past Developments...................12 3.4 Advancements in Natural Language Processing Algorithms for Movie Industry Analysis...................................................................................................................................13 3.5 Machine Learning in the Movie Industry: Post-COVID Shifts and Trends.....................15 3.6 Machine Learning Applications in the Airline Industry: Pre-COVID Insights................16 3.7 ML's Applications in the Airline Industry Post-COVID........................................18 3.8 Implications of Machine Learning Techniques in Dynamic Environments..................19 3.9 Impact of COVID-19 on Machine Learning Applications in the Movie and Airline Industries............................................................................................................21 Results and Discussion 4.1 Impact of COVID-19 on the Movie Industry: Shifting Trends and Environments........22 4.2 Challenges of ML Models in the Movie Industry................................................23 4.3 Airline Industry during the COVID-19 Crisis: Challenges and Adaptations...............25 4.4 Impact of COVID-19 on Flight Operations Post-Covid.......................................25 Conclusion 5.1 Summary of the main findings of the study and outlook..................................................26 References..............................................................................................................................28
    Language: Undetermined
    Keywords: Academic theses
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  • 9
    UID:
    kobvindex_INT60872
    Format: 40 pages : , illustrations ; , 21 × 29.7 cm.
    Content: AI-GENERATED ABSTRACT: Abstract: This paper aims to build a machine learning model to forecast consumer revenge spending behavior in the post Covid-19 travel industry. Covid-19 has created a new phenomenon "Revenge Spending", where consumers spend excessively in order to compensate for the negative emotion and constraint experienced during the pandemic. This study utilized travel related factors like travel intentions and financial variables to train the machine learning models which included Logistic Regression, Random Forest and Decision Trees. To evaluate which predictive model performs the best in predicting consumer revenge spending behavior in post pandemic travel, cross-validation techniques, accuracy, precision, recall, F1-score, and AUC-ROC metrics were used. The findings of the study bring a meaningful understanding of consumer revenge spending behavior in travel and offer some insight on the key features that are influencing this behavior. Keywords: consumer revenge spending, post Covid-19, travel industry, machine learning, Logistic Regression, Random Forest, Decision Trees, predictive modeling, evaluation metrics, travel behavior
    Note: DISSERTATION NOTE: Bachelor of Arts thesis in Digital Business and Management, Berlin International University of Applied Sciences, 2023. , MACHINE-GENERATED CONTENTS NOTE: Table of Contents abstract..........................................................................2 1. Introduction.................................................................2 2. Literature Review..........................................................3 2.1. Definition of Consumer Revenge Spending Behavior.............3 2.2. Consumer Revenge Spending Behavior in Travel.................4 2.3. the Significance of Understanding Change in Consumer Behavior in the Post Covid-19 Travel Industry...................4 2.4. Utilizing Machine Learning Techniques to Predict Consumer Behavior.................................................................5 2.5. Machine Learning Approaches: Strengths and Limitations.....6 2.6. Evaluation Metrics.....................................................8 2.7. Research Gaps and Limitation......................................8 2.8. Hypotheses Development............................................9 3. Method...................................................................10 3.1. Survey Design and Approach......................................11 3.2. Data Collection Process.............................................12 3.3. Data Pre-processing...................................................12 3.4. Machine Learning Methods.........................................13 4. Data Analysis..............................................................13 4.1. Overview of the Dataset and Data Exploration.....................13 4.2. Testing 1st Hypothesis: Revenge Spending and Desire of Travel.20 4.3. Testing 2nd Hypothesis: Cautious Spending and Financial Factors21 4.4. Correlation of Revenge Spending and All Variables................22 4.5. Feature Selection......................................................23 5. Results...................................................................25 5.1. Model Performance and Comparison...............................25 5.2. Cross-validation.......................................................26 5.3. Testing Final Hypothesis.............................................27 6. Discussion.................................................................28 6.1. Theoretical Implications..............................................28 6.2. Practical Implications................................................28 6.3. Limitations and Future Research...................................29 7. Conclusion.................................................................29 references...................................................................31 appendix 1 - List of Variables - Explanation..............................34 appendix 2 - Survey..........................................................35
    Language: Undetermined
    Keywords: Academic theses
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  • 10
    UID:
    kobvindex_INT61026
    Format: 38 pages : , illustrations ; , 21.59 × 27.94 cm.
    Content: AUTHOR-SUPPLIED ABSTRACT: Abstract Companies are increasingly interested in finding ways to attract and retain talent, which, in today's competitive landscape, is the safest bet that can be made to reach a competitive advantage. However, the increasing amount of data available and the changing needs within the workforce make the traditional approaches to Talent Acquisition (TA) outdated. To address the current challenges of TA, specialists should leverage Data Analytics to gain valuable insights. Based on existing literature reviews and the specific case study of Zalando, the purpose of this research is to understand what the current main challenges of TA are and to analyze how Zalando approaches these challenges in terms of Data Analytics. Through interviews with Zalando's Talent Acquisition experts, results indicate that, while TA specialists are progressively intrigued in implementing these solutions, there are still many deficiencies in the company as a whole that do not allow for the full integration of Data Analytics. Zalando is not yet at a level of analytics maturity that allows Talent Acquisition to completely leverage Data Analytics. However, solving operational challenges first can lead to the development of models of advanced Data Analytics that could differentiate Zalando from the competition. Keywords: Data Analytics, Talent Acquisition, talent, challenges, data, Zalando
    Note: DISSERTATION NOTE: Bachelor of Arts thesis in Business Administration - International Management and Marketing, Berlin International University of Applied Sciences, 2022. , MACHINE-GENERATED CONTENTS NOTE: Table of Contents Abstract Introduction 2. Literature Review 2.1 Data Science and Analytics 2.2 Talent Acquisition 2.2.1 Challenges of Talent Acquisition 2.4 Talent Analytics 2.5 Zalando 3. Methodology 3.1 Research Purpose 3.2 Research Approach 3.3 Research Design 3.4 Data Collection 3.4.1 The Interviews 3.5 Data Analysis 4. Results and Analysis 4.1 Theme 1: Process 4.1.1 Lead Time 4.1.2 Hiring Bottlenecks 4.1.3 Candidate Sources 4.1.4 Diversity 4.1.5 Attrition 4.2 Theme 2: People 4.2.1 Biases 4.2.2 Support 4.2.3 Interviewer Accuracy 4.3 Theme 3: Business 4.3.1 Future Employment Needs 4.3.2 Alignment 4.3.3 Costs 5. Discussion 6. Conclusion References Appendices
    Language: Undetermined
    Keywords: Academic theses
    URL: FULL
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