67 research outputs found

    Identification and Interpretation of the Importance of Customer Service Satisfaction Factors

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    Customer satisfaction is shaped by their experience over the whole supplier - customer relation cycle, i.e., throughout a pre-transactional, transactional and post-transactional phase, respectively. Customer service is the process that unites all three phases. Therefore planning efficient customer service should be based on the priorities which customers value most in the process and which have the strongest impact on their satisfaction. The literature and practice indicate at least two ways which allow one to establish customer-perceived significance of market offerings’ attributes. However, each way leads to a different customer’s reality and supports different managerial decisions. Understanding of those alternative ways enables decision-makers to take more appropriate steps and consequently achieve higher levels of customer satisfaction. In this article, we attempt to uncover the implications of alternative procedures to identify customer perceived importance of market offering aspects: stated importance and derived importance. We verify our claims using the data from an exploratory study of personal insulin pumps users

    Digestion, defecation and food passage rate in the insectivorous bat Myotis myotis

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    Collection life cycle analysis : enhancing market strategies through advanced data analytics

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    PURPOSE: This study introduces an analytical application designed to deeply analyze the product life cycle and optimize a business's marketing and operational strategies. The primary objective of this application is to help companies effectively identify and navigate the various phases of a product's life, from launch to growth, maturity, and decline.DESIGN/METHODOLOGY/APPROACH: The application features interactive tools, such as sales value maps and animations illustrating changes in selected indicators, to enable real-time sales data analysis and forecast future trends using the Prophet model. The article elaborates on the application's capabilities, including statistical analysis of selected collections like average sales value, number of orders, storage costs, and the effects of seasonality and special promotional periods on sales outcomes.FINDINGS: The study highlights how this application aids businesses in adapting their strategies to dynamically changing market conditions, enabling efficient resource management and maximizing profitability.PRACTICAL IMPLICATIONS: The article presents the application's functionalities and emphasizes its value in adjusting business strategies to rapidly changing market conditions. It underlines the significance of using advanced analytical tools for informed decision-making, which can contribute to the company's enduring success.ORIGINALITY/VALUE: This work presents an innovative analytical tool that provides businesses with crucial insights for adapting their marketing and operational strategies. It adds value by demonstrating the importance of leveraging advanced analytics in decision-making to ensure long-term business success in fluctuating market environments.peer-reviewe

    Evaluating the effectiveness of advertising campaigns in the fast-food industry using an analytical engine

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    PURPOSE: The primary objective of this research is to explore the effectiveness of marketing campaigns using an analytics engine capable of processing and interpreting complex data sets. The study focuses on a specific case within the fast-food industry, where traditional marketing strategies are employed to promote new product launches.DESIGN/METHODOLOGY/APPROACH: The methodology employed in this research entails a comprehensive analysis of a dataset titled 'Fast-food Marketing Campaign,' which records sales outcomes from various marketing initiatives across multiple locations. The dataset encompasses market size, location, promotion type, and weekly sales figures, offering a comprehensive view of the campaign's reach and effectiveness. This study utilizes descriptive statistics, predictive modeling through Light GBM (an enhanced decision tree algorithm), and regression analysis to identify key factors that influence the success of traditional marketing campaigns. Moreover, a user-friendly interface was developed using the Dash programming framework, ensuring marketers can easily visualize and interpret the analysis results.FINDINGS: Descriptive analysis highlighted the variability in sales and store characteristics, while predictive analysis showed the model's ability to forecast sales outcomes accurately. Regression analysis further identified the most influential variables affecting campaign success, such as market size and specific promotions. The model's predictions aligned with actual sales data, confirming its effectiveness in capturing underlying data patterns and contributing to strategic marketing decisions.PRACTICAL IMPLICATIONS: This research holds substantial practical implications for marketing professionals, particularly in sectors where traditional campaigns continue to be pivotal. The development of an analytical interface enables dynamic data exploration, empowering marketers to make informed decisions based on comprehensive analysis results. This tool can significantly bolster the planning and execution of marketing strategies by providing insights into the factors that most significantly impact campaign success, thereby optimizing marketing investments and strategies.ORIGINALITY/VALUE: This study's originality lies in its focused examination of traditional marketing campaigns within the context of a modern data analytics framework. By integrating advanced analytical techniques with traditional marketing data, this research bridges the gap between conventional marketing approaches and contemporary analytical methodologies.peer-reviewe

    Metody i obszary zarządzania

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    Publikacja recenzowana / Peer-reviewed publicationOpracowanie poświęcone jest charakterystyce i propozycji rozwiązania wybranych problemów zarządzania. Kilka tekstów dotyczy roli mediów (a także innych instrumentów) w marketingu. Ciekawe jest opracowanie oparte na pewnej autorskiej typologii instrumentów marketingu-mix stosowych przez przedsiębiorstwa działające na rynkach zagranicznych. Druga grupa artykułów poświęcona jest nowym formom zatrudnienia, partycypacji pracowników oraz standardów ochrony pracy, które winny być stosowane przez nasze organizacje. Zatem blok ten dotyczy zagadnień organizacji pracy. Są także artykuły prezentujące konkretne metody zarządzania, począwszy od zarządzania komunikacją, przez zarządzanie strategiczne, a na systemach zarządzania produkcją skończywszy. Niektórzy Autorzy podejmują się nie tylko prezentacji, a także przedstawiają pewne rozwiązania zagadnień dotyczących niemal wszystkich obywateli. Tu przede wszystkim należy wymienić rozważania o kształtowaniu tran sportu publicznego. Ciekawe jest także studium o możliwości wykorzystania Internetu na rynku ubezpieczeń społecznych

    Actinoid pnictides--II : Heat capacities of UAs2 and USb2 from 5 to 750 K and antiferromagnetic transitions

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    The heat capacities of uranium diarsenide (UAs2) and uranium diantimonide (USb2), with tetragonal structures of the anti-Cu2Sb-type, have been measured by adiabatic-shield calorimetry from 5 to about 750 K. Lambda-type transitions with maxima at 272.2 and 202.5 K for UAs2 and USb2, respectively, are related to maxima in the magnetic susceptibilities at 277 and 203 K, occasioned by transitions from antiferro- to paramagnetism in the compounds. Values of the heat capacities (Cp), entropies [S[deg](T) - S[deg](0)], and Gibbs energy functions -{[G[deg](T) - H[deg](o)]/T} at 298.15 K in cal K-1 mole-1 are 19.12, 29.41 and 15.05 for UAs2 and 19.16, 33.81 and 18.39 for USb2. Tentative resolutions of the cooperative magnetic heat capacities of UAs2 and USb2 lead to the magnetic entropies [Delta]S(mag) = 0.99 and 1.70 cal K-1 mole-1, respectively. The values for both are significantly lower than the spin-only magnetic entropy value R ln 3 = 2.18 cal K-1 mole-1.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/22763/1/0000318.pd
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