12,588 research outputs found

    Quantifying and Explaining Machine Learning Uncertainty in Predictive Process Monitoring: An Operations Research Perspective

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    This paper introduces a comprehensive, multi-stage machine learning methodology that effectively integrates information systems and artificial intelligence to enhance decision-making processes within the domain of operations research. The proposed framework adeptly addresses common limitations of existing solutions, such as the neglect of data-driven estimation for vital production parameters, exclusive generation of point forecasts without considering model uncertainty, and lacking explanations regarding the sources of such uncertainty. Our approach employs Quantile Regression Forests for generating interval predictions, alongside both local and global variants of SHapley Additive Explanations for the examined predictive process monitoring problem. The practical applicability of the proposed methodology is substantiated through a real-world production planning case study, emphasizing the potential of prescriptive analytics in refining decision-making procedures. This paper accentuates the imperative of addressing these challenges to fully harness the extensive and rich data resources accessible for well-informed decision-making

    HR Analytics: Concept, Application, and Impact on Talent Management, Branding, and Challenges

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    Purpose: Making wiser decisions about employees to improve performance at the individual and/or organizational levels is the process of HR analytics. HR analytics is a method for determining the correlation between HR practices and organizational performance outcomes such as sales volume or customer satisfaction. Human Resource Analytics was established in 1978 by Jac Fitz-Enz, the pioneer of human capital strategic analysis and performance benchmarking. In this paper, the researcher wants to discuss the concept of HR analytics, its application, impact on talent management, branding, and challenges in its application.Design/methodology/approach: The researcher examines secondary data and conducts a thorough literature review to understand the concept and its application across industries and nations, as well as to identify any challenges encountered during deployment and any benefits perceived by various industry professionals. Findings: The study's findings indicate that using HR analytics can help businesses build their brand and gain a competitive edge in today's fiercely competitive business environment while also enhancing workforce and employee productivity.Originality/value: This study has significant implications for both literature and HR analytics. Researchers will know more about the factors that contribute to and the mechanisms by which HR analytics improve organisational performance. The author's second claim is that having access to HR technology both facilitates and precedes HR analytics. Finally, concrete data from the literature demonstrates its influence on branding and organisational success. Keywords: Human resource (HR) analytics, People analytics, Branding, Talent Management, Organizational performance. Paper type: Research paper JEL Code: M12, M15 & M51 DOI: 10.7176/EJBM/15-8-06 Publication date: April 30th 202

    A Design Science Research Approach to Smart and Collaborative Urban Supply Networks

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    Urban supply networks are facing increasing demands and challenges and thus constitute a relevant field for research and practical development. Supply chain management holds enormous potential and relevance for society and everyday life as the flow of goods and information are important economic functions. Being a heterogeneous field, the literature base of supply chain management research is difficult to manage and navigate. Disruptive digital technologies and the implementation of cross-network information analysis and sharing drive the need for new organisational and technological approaches. Practical issues are manifold and include mega trends such as digital transformation, urbanisation, and environmental awareness. A promising approach to solving these problems is the realisation of smart and collaborative supply networks. The growth of artificial intelligence applications in recent years has led to a wide range of applications in a variety of domains. However, the potential of artificial intelligence utilisation in supply chain management has not yet been fully exploited. Similarly, value creation increasingly takes place in networked value creation cycles that have become continuously more collaborative, complex, and dynamic as interactions in business processes involving information technologies have become more intense. Following a design science research approach this cumulative thesis comprises the development and discussion of four artefacts for the analysis and advancement of smart and collaborative urban supply networks. This thesis aims to highlight the potential of artificial intelligence-based supply networks, to advance data-driven inter-organisational collaboration, and to improve last mile supply network sustainability. Based on thorough machine learning and systematic literature reviews, reference and system dynamics modelling, simulation, and qualitative empirical research, the artefacts provide a valuable contribution to research and practice

    Quality cost flows in manufacturing companies

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    Companies have increasingly focused their attention on quality costs. Therefore, raising awareness of this group of expenses is essential. This paper aims to present a survey on the topic of costs of quality management in manufacturing companies in the Czech Republic. This paper opens with a literature review that focuses on the existing cost of quality models and then focuses on empirical research results. Manufacturing companies represent the framework of this research. The research with a total of 159 respondents provides information about the real market situation. The aim was to determine the significance of costs and cost-effectiveness. The study's findings revealed that 73% of organizations quantify their quality costs completely, 21% of companies quantify their costs only partly (external costs), and 6% of companies do not. 36% of surveyed companies (42 companies) that monitor quality costs use some of the recommended models, mainly the PAF model. The research was confirmed by hypothesis 1 that companies that use some type of evidence cost of quality have lower levels of these costs.Internal Grant Agency of FaME TBU; [IGA/FaME/2021/014

    Sponsorship of individual athletes in relation to the company’s marketing strategy

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    Abstract. Sports marketing is constantly evolving and its importance as a marketing tool is strengthening worldwide. As a result, sponsorship of individual athletes and personal brands have become strategic marketing tools for companies. The marketing strategy of companies should follow and support the overall strategy of the company, therefore marketing measures, such as, sponsorship should also follow and support the overall strategy. Previous research has examined sponsorship from the perspective of value creation as well as from the perspective of how sponsorship affects the corporate image and the benefits of sponsorship for stakeholders. In terms of strategy, sponsorship has been examined from the perspective of what kind of sponsorship strategies companies have. Sponsorship in general and the sponsorship of individual athletes as its sub-theme are still very little studied themes in Finland. Therefore, comprehensive data is required on how sponsorship can be utilized as a strategic tool in marketing. The aim of the study is to investigate how the sponsorship of individual athletes in Finland is linked to the marketing strategy of companies. Interviewing Finnish companies is of primary importance for researching this topic. The research follows an abductive process, which means that the existing literature is studied first, and the empirical analysis is conducted based on the formed theoretical framework. The research is a qualitative multiple-case study, and the empirical data is collected through five semi-structured interviews with company representatives of large and medium-sized enterprises of various business sectors. Based on the data, companies perceive individual athlete sponsorship either as an embedded part of a marketing strategy, as partially embedded marketing measure, or as not in relation to marketing strategy. This is influenced by factors, such as, industry, the size of the sponsorship agreement, the athletes’ own motivation, and the companies’ ability or inability to utilize individual athletes in the company’s marketing communications. Sponsorship of individual athletes was seen as a regionally significant factor from the perspective of corporate social responsibility

    Product-service systems and circular supply chain practices in UK SMEs: The moderating effect of internal environmental orientation

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    Many studies uphold product-service systems (PSSs) as key factors for the implementation of circular supply chain (CSC) practices. This paper explores this assumption by testing the links between product-, use- and result-oriented PSSs and slowing, closing, and narrowing CSC practices. It develops and validates survey items that can be used to benchmark CSC practice implementation. In addition, it tests a model that recognises the positive moderating role of internal environmental orientation. A survey is conducted with 114 manufacturing small and medium-sized enterprises (SMEs) in the United Kingdom (UK). Partial least squares structural equation modelling is conducted to evaluate two models. The results show that product-oriented PSSs positively affect the slowing, use-oriented positively affects the closing, and result-oriented positively affects the slowing and the narrowing of resource loops. Internal environmental orientation does not moderate the PSS – CSC relationship, suggesting that less internally environmentally oriented firms are not at a disadvantage

    AI-based Conversational Agents for Customer Service – A Study of Customer Service Representative’ Perceptions Using TAM 2

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    This study aimed to identify the various factors that may influence customer service representatives’ perceptions of artificial intelligence (AI)-based conversational agents (CAs) for customer service. By analyzing 180 publications, a conceptual research model is developed for identifying the factors that may influence customer service representatives’ perceptions of AI-based CAs for customer service. The underlying conceptual research model comprises ten factors. The study is grounded in the application of the Technology Acceptance Model 2 (TAM 2) approach. The research model is empirically evaluated with survey data from 128 participants. Our results show that the direct positive effect of subjective norm on customer service representatives’ perception of using AIbased CAs in customer service decreases with increasing experience. Moreover, our results reveal new insights regarding trust. The results of this study provide an overview of the predominant characteristics of the influencing factors of customer service representatives’ perceptions of AI-based CAs for customer service
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