524 research outputs found

    Employing A-B Tests for Optimizing Prices Levels in eCommerce Applications

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    Price dispersion in the Internet is a well studied phenomenon. It enables companies to adjust prices to a level appropriate to their strategy. This paper deals with question how Internet retailers should do so. The discussed method optimizes short- and long-term profitability by determining the exact demand curve. The method involves the application of empirical price tests. For this purpose visitors of an Internet retailer are divided in statistically identical subgroups. Using the A-B testing method different prices are shown to each subgroup and the conversion rate as a function of price is calculated. We describe the organizational requirements, the technical approach, and the statistical analysis applied to determine the price optimizing the per-order profit and the average customer lifetime value. A field study carried out with a large Internet retailer is presented and shows that the company was able to optimize a specific price component and thus increase the contribution margin per order by about 7% while at the same time the customer lifetime value could be enhanced by 13%. We conclude that the discussed method could be applied to answer further research questions such as the temporal variation of demand curves

    The First 25 Years of the Bled eConference: Themes and Impacts

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    The Bled eConference is the longest-running themed conference associated with the Information Systems discipline. The focus throughout its first quarter-century has been the application of electronic tools, migrating progressively from Electronic Data Interchange (EDI) via Inter-Organisational Systems (IOS) and eCommerce to encompass all aspects of the use of networking facilities in industry and government, and more recently by individuals, groups and society as a whole. This paper reports on an examination of the conference titles and of the titles and abstracts of the 773 refereed papers published in the Proceedings since 1995. This identified a long and strong focus on categories of electronic business and corporate perspectives, which has broadened in recent years to encompass the democratic, the social and the personal. The conference\u27s extend well beyond the papers and their thousands of citations and tens of thousands of downloads. Other impacts have included innovative forms of support for the development of large numbers of graduate students, and the many international research collaborations that have been conceived and developed in a beautiful lake-side setting in Slovenia

    International Conference on Management Business and Economy

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    UBT Annual International Conference is the 11th international interdisciplinary peer reviewed conference which publishes works of the scientists as well as practitioners in the area where UBT is active in Education, Research and Development. The UBT aims to implement an integrated strategy to establish itself as an internationally competitive, research-intensive university, committed to the transfer of knowledge and the provision of a world-class education to the most talented students from all background. The main perspective of the conference is to connect the scientists and practitioners from different disciplines in the same place and make them be aware of the recent advancements in different research fields, and provide them with a unique forum to share their experiences. It is also the place to support the new academic staff for doing research and publish their work in international standard level. This conference consists of sub conferences in different fields like: Art and Digital Media Agriculture, Food Science and Technology Architecture and Spatial Planning Civil Engineering, Infrastructure and Environment Computer Science and Communication Engineering Dental Sciences Education and Development Energy Efficiency Engineering Integrated Design Information Systems and Security Journalism, Media and Communication Law Language and Culture Management, Business and Economics Modern Music, Digital Production and Management Medicine and Nursing Mechatronics, System Engineering and Robotics Pharmaceutical and Natural Sciences Political Science Psychology Sport, Health and Society Security Studies This conference is the major scientific event of the UBT. It is organizing annually and always in cooperation with the partner universities from the region and Europe. We have to thank all Authors, partners, sponsors and also the conference organizing team making this event a real international scientific event. Edmond Hajrizi, President of UBT UBT – Higher Education Institutio

    Maximizing User Engagement In Short Marketing Campaigns Within An Online Living Lab: A Reinforcement Learning Perspective

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    ABSTRACT MAXIMIZING USER ENGAGEMENT IN SHORT MARKETING CAMPAIGNS WITHIN AN ONLINE LIVING LAB: A REINFORCEMENT LEARNING PERSPECTIVE by ANIEKAN MICHAEL INI-ABASI August 2021 Advisor: Dr. Ratna Babu Chinnam Major: Industrial & Systems Engineering Degree: Doctor of Philosophy User engagement has emerged as the engine driving online business growth. Many firms have pay incentives tied to engagement and growth metrics. These corporations are turning to recommender systems as the tool of choice in the business of maximizing engagement. LinkedIn reported a 40% higher email response with the introduction of a new recommender system. At Amazon 35% of sales originate from recommendations, while Netflix reports that ‘75% of what people watch is from some sort of recommendation,’ with an estimated business value of 1billionperyear.Whiletheleadingcompanieshavebeenquitesuccessfulatharnessingthepowerofrecommenderstoboostuserengagementacrossthedigitalecosystem,smallandmediumbusinesses(SMB)arestrugglingwithdecliningengagementacrossmanychannelsascompetitionforuserattentionintensifies.TheSMBsoftenlackthetechnicalexpertiseandbigdatainfrastructurenecessarytooperationalizerecommendersystems.Thepurposeofthisstudyistoexplorethemethodsofbuildingalearningagentthatcanbeusedtopersonalizeapersuasiverequesttomaximizeuserengagementinadata−efficientsetting.Weframethetaskasasequentialdecision−makingproblem,modelledasMDP,andsolvedusingageneralizedreinforcementlearning(RL)algorithm.Weleverageanapproachthateliminatesoratleastgreatlyreducestheneedformassiveamountsoftrainingdata,thusmovingawayfromapurelydata−drivenapproach.Byincorporatingdomainknowledgefromtheliteratureonpersuasionintothemessagecomposition,weareabletotraintheRLagentinasampleefficientandoperantmanner.Inourmethodology,theRLagentnominatesacandidatefromacatalogofpersuasionprinciplestodrivehigheruserresponseandengagement.ToenabletheeffectiveuseofRLinourspecificsetting,wefirstbuildareducedstatespacerepresentationbycompressingthedatausinganexponentialmovingaveragescheme.AregularizedDQNagentisdeployedtolearnanoptimalpolicy,whichisthenappliedinrecommendingone(oracombination)ofsixuniversalprinciplesmostlikelytotriggerresponsesfromusersduringthenextmessagecycle.Inthisstudy,emailmessagingisusedasthevehicletodeliverpersuasionprinciplestotheuser.Atatimeofdecliningclick−throughrateswithmarketingemails,businessexecutivescontinuetoshowheightenedinterestintheemailchannelowingtohigher−than−usualreturnoninvestmentof1 billion per year. While the leading companies have been quite successful at harnessing the power of recommenders to boost user engagement across the digital ecosystem, small and medium businesses (SMB) are struggling with declining engagement across many channels as competition for user attention intensifies. The SMBs often lack the technical expertise and big data infrastructure necessary to operationalize recommender systems. The purpose of this study is to explore the methods of building a learning agent that can be used to personalize a persuasive request to maximize user engagement in a data-efficient setting. We frame the task as a sequential decision-making problem, modelled as MDP, and solved using a generalized reinforcement learning (RL) algorithm. We leverage an approach that eliminates or at least greatly reduces the need for massive amounts of training data, thus moving away from a purely data-driven approach. By incorporating domain knowledge from the literature on persuasion into the message composition, we are able to train the RL agent in a sample efficient and operant manner. In our methodology, the RL agent nominates a candidate from a catalog of persuasion principles to drive higher user response and engagement. To enable the effective use of RL in our specific setting, we first build a reduced state space representation by compressing the data using an exponential moving average scheme. A regularized DQN agent is deployed to learn an optimal policy, which is then applied in recommending one (or a combination) of six universal principles most likely to trigger responses from users during the next message cycle. In this study, email messaging is used as the vehicle to deliver persuasion principles to the user. At a time of declining click-through rates with marketing emails, business executives continue to show heightened interest in the email channel owing to higher-than-usual return on investment of 42 for every dollar spent when compared to other marketing channels such as social media. Coupled with the state space transformation, our novel regularized Deep Q-learning (DQN) agent was able to train and perform well based on a few observed users’ responses. First, we explored the average positive effect of using persuasion-based messages in a live email marketing campaign, without deploying a learning algorithm to recommend the influence principles. The selection of persuasion tactics was done heuristically, using only domain knowledge. Our results suggest that embedding certain principles of persuasion in campaign emails can significantly increase user engagement for an online business (and have a positive impact on revenues) without putting pressure on marketing or advertising budgets. During the study, the store had a customer retention rate of 76% and sales grew by a half-million dollars from the three field trials combined. The key assumption was that users are predisposed to respond to certain persuasion principles and learning the right principles to incorporate in the message header or body copy would lead to higher response and engagement. With the hypothesis validated, we set forth to build a DQN agent to recommend candidate actions from a catalog of persuasion principles most likely to drive higher engagement in the next messaging cycle. A simulation and a real live campaign are implemented to verify the proposed methodology. The results demonstrate the agent’s superior performance compared to a human expert and a control baseline by a significant margin (~ up to 300%). As the quest for effective methods and tools to maximize user engagement intensifies, our methodology could help to boost user engagement for struggling SMBs without prohibitive increase in costs, by enabling the targeting of messages (with the right persuasion principle) to the right user

    DIGITAL WINE: HOW PLATFORMS AND ALGORITHMS WILL RESHAPE THE WINE INDUSTRY

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    La tesi si propone di analizzare come la digitalizzazione e gli approcci basati sui dati, in particolare quelli che sfruttano l'intelligenza artificiale, stiano impattando il settore vitivinicolo e facendo emergere modelli nuovi di business. Quest'ultimo aspetto sarà approfondito tramite due casi studio di piattaforme digitali che, attraverso approcci diversi, stanno contribuendo a generare un ecosistema digitale virtuoso, con potenziali benefici per tutta la catena del valore a livello di settore.The thesis aims to analyze how digitalization and data-driven approaches, in particular those that leverage artificial intelligence, are impacting the wine industry and generating new business models. The latter aspect will be explored through two case studies of digital platforms which, through different approaches, are helping to generate a virtuous digital ecosystem, with potential benefits for the entire value chain at the industry level

    Business plan for an innovative feminine medical device

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    The gynecological area related to vaginal infections is not very explored from the practical point of view of the patient. The range of options of self-testing kits is limited and little publicized, so women tend to go to the doctor whenever they feel any discomfort, or they simply buy medicine without a prescription. Therefore, a market opportunity arises to fill the lack of public information about this often neglected area of their personal health, without having to consult a doctor. This thesis explores the Femtech and Medtech market in Portugal and Europe. The business plan is about the launching of an innovative medical device to self-test vaginal infections and which connects to a mobile app to create records and analyticaly analyse the test results. This product’s aim is therefore to promote women’s well-being and health, allying with technology to inform them and subsequently help them to make decisions regarding their gynecological health.A área ginecológica relacionada com as infeções vaginais apresenta-se pouco explorada do ponto de vista prático do paciente. O leque de opções de testes de auto-diagnóstico é limitado e pouco divulgado, o que leva a que as mulheres tenham o hábito de consultar o médico quando sentem algum desconforto ou comprar um medicamento sem receita médica. Assim, surge uma oportunidade no mercado de colmatar a falta de informação do público sobre esta área da sua saúde pessoal, muitas vezes negligenciada, sem ter de recorrer a uma consulta médica. Esta tese explora os mercados das Femtech e Medtech, em Portugal e no resto da Europa. O plano de negócios desenvolvido diz respeito ao lançamento de um dispositivo médico inovador para auto-diagnosticar infeções vaginais. Este tem conexão com uma app móvel, de forma a criar um histórico e analisar analiticamente os resultados dos testes. O objetivo deste produto é, assim, promover o bem-estar e a saúde da mulher, aliando-se à tecnologia para a informar e, consequentemente, a ajudar a tomar decisões no que diz respeito à sua saúde ginecológica

    Data-driven Warehouse Management in Global Supply Chains

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