Essays about: "Spending Behavior"

Showing result 1 - 5 of 44 essays containing the words Spending Behavior.

  1. 1. "Den 25:e smäller det!" Payday Arbitrage in Swedish Consumer Market Behavior

    University essay from Handelshögskolan i Stockholm/Institutionen för finansiell ekonomi

    Author : Marwan Al-Bardaji; Alexander Wikström; [2023]
    Keywords : Payday effect; Behavioral household finance; Time preference; Payday arbitrage; Household liquidity;

    Abstract : This thesis investigates the impact of the Swedish salary disbursement schedule on consumer behavior, particularly on the 25th of each month, a notable payday for most employees in Sweden. The study examines whether the anticipation of a monthly salary influences consumer decisions and spending patterns, potentially leading to payday-related arbitrage opportunities in Swedish marketplaces. READ MORE

  3. 2. Second hand + Online + Gen Z = TRUE : A quantitative study on the motivations behind second-hand shopping for clothes online

    University essay from Umeå universitet/Företagsekonomi

    Author : Amanda Häggmark; Fanny Olofsson; [2023]
    Keywords : Online shopping second-hand; Generation Z; Impulse Buying Tendency; Perceived Risk; Shopping Motives;

    Abstract : The environmental issues in the world are critical and sustainability becomes more important. There is a certain lack in the textile industry, where the production of clothes is responsible for water pollution, landfill waste and greenhouse gas emission. READ MORE

  4. 3. The Innovation Game: A study of the relationship between CEO compensation and R&D spending

    University essay from Handelshögskolan i Stockholm/Institutionen för finansiell ekonomi

    Author : Joakim Edlund; Andreas Olsson; [2023]
    Keywords : CEO; Compensation; Risk-taking; Research Development; Options;

    Abstract : While previous research has examined how CEO compensation influences managerial behavior, little is known about whether and how compensation influences R&D spending decisions. Because theoretical models predict that CEOs are disincentivized to undertake projects with uncertain long-term payoffs, scholars argue that CEO compensation should be linked to long-term performance. READ MORE

  5. 4. Predicting Customer Churn in E-commerce Using Statistical Modeling and Feature Importance Analysis : A Comparison of Random Forest and Logistic Regression Approaches

    University essay from Umeå universitet/Institutionen för matematik och matematisk statistik

    Author : Amanda Rudälv; [2023]
    Keywords : Customer behavior; E-commerce; Churn prediction; Statistical model; Machine learning; Random forest; Logistic regression; Feature importance; Kundbeteende; E-handel; Kundbortfall; Statistisk modell; Maskininlärning; Random forest; Logistisk regression; Variabelsignifikans;

    Abstract : While operating in online markets offers opportunities for expanded assortment and convenience, it also poses challenges such as increased competition and the need to build personal relationships with customers. Customer retention be- comes crucial in maintaining a successful business, emphasizing the importance of understanding customer behavior. READ MORE

  6. 5. Classification Method of Financial Behaviour Through Means of Machine Learning : Can a classification method created using bank transaction and machine learning help individuals to understand their spending behavior?

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Yilei Cheng; Akhmed Al-Sayed; [2022]
    Keywords : machine learning; bank transactions; classification; spending behaviour; overspending; money awareness.; maskininlärning; banktransaktioner; klassificering; utgiftsbeteende; överutgifter; finansiell kunskap.;

    Abstract : With the current fast transformation from physical cash to digitized banking systems, there are more and more people that are at risk of overspending without realizing it. There are methods and researches done that are targeted at incorporating machine learning in identifying fraudulent transactions and credit scores but currently there is no research done in categorizing people’s behaviour based on transaction records using machine learning techniques. READ MORE