Suchergebnisse

This thesis is about consumer acceptance of products consisting of materials which are based on renewable resources. The focus is on wood-based materials, including solid wood but also by-products and wood waste, as only the combination of these materials facilitates resource efficiency. The thesis differs between traditional (e.g., solid wood, particleboards) and innovative (e.g., Wood-Polymer Composites (WPCs)) wood-based materials, with different research questions arising while depending on the material's novelty. Three studies address the derived research questions. Considering traditi...

This thesis is about consumer acceptance of products consisting of materials which are based on renewable resources. The focus is on wood-based materials, including solid wood but also by-products and wood waste, as only the combination of these materials facilitates resource efficiency. The thesis differs between traditional (e.g., solid wood, particleboards) and innovative (e.g., Wood-Polymer Composites (WPCs)) wood-based materials, with different research questions arising while depending on the material's novelty. Three studies address the derived research questions. Considering traditi...

Service organizations, emboldened by the imperative to innovate, are increasingly introducing robots to frontline service encounters. However, as they augment or substitute human employees with robots, they may struggle to convince a distrusting public of their brand's ethical credentials. Consequently, this article develops and tests a holistic framework to ascertain a deeper understanding of customer perceptions of frontline service robots (FLSRs) than has previously been attempted. Our experimental studies investigate the effects of the (1) role (augmentation or substitution of human employees or no involvement) and (2) type (humanoid FLSR vs. self-service machine) of FLSRs under the following service contexts: (a) value creation model (asset-builder, service provider) and (b) service type (experience, credence). By empirically establishing our framework, we highlight how customers' personal characteristics ( openness-to-change and preference for ethical/responsible service provider) and cognitive evaluations ( perceived innovativeness, perceived ethical/societal reputation, and perceived innovativeness-responsibility fit) influence the impact that FLSRs have on service experience and brand usage intent. Our findings operationalize and empirically support seminal frameworks from extant literature, as well as elaborate on the positive and negative implications of using robots to complement or replace service employees. Further, we consider managerial and policy implications for service in the age of machines.

Advances in artificial intelligence (AI) are increasingly enabling firms to develop services that utilize autonomous vehicles (AVs). Yet, there are significant psychological barriers to adoption, and insights from extant literature are insufficient to understand customer emotions regarding AV services. To allow for a holistic exploration of customer perspectives, we synthesize multidisciplinary literature to develop the Customer Responses to Unmanned Intelligent-transport Services based on Emotions (CRUISE) framework, which lays the foundation for improved strategizing, targeting, and positioning of AV services. We subsequently provide empirical support for several propositions underpinning the CRUISE framework using representative multinational panel data ( N = 27,565) and an implicit association test ( N = 300). We discover four distinct customer segments based on their preferred degree of service autonomy and service risk. The segments also differ in terms of the valence and intensity of emotional responses to fully autonomous vehicle services. Additionally, exposure to positive information about AV services negatively correlates with the likelihood of membership in the two most resistant segments. Our contribution to service research is chiefly twofold; we provide: 1) a formal treatise of AV services, emphasizing their uniqueness and breadth of application, and 2) empirically validated managerial directions for effective strategizing based on the CRUISE framework.

© 2017 Elsevier Ltd Despite growing consumer awareness of ethical consumption, market sales are not growing accordingly. Because the presentation of appropriate ethical product information may influence consumers to choose ethical products, this paper analyses the requirements necessary for the successful communication of ethical product features. Based on McGuire's (1976) information-processing model, and a review of current literature, the information's comprehensibility, meaningfulness, and credibility are investigated in an online survey of US American citizens (n = 595) for two product categories representing Fast Moving Consumer Goods, and durable goods. A generalized mixed logit model revealed that all three communication factors affect consumers' choices. The more concerns about, or expertise in, organic production and fair trade purchase the consumers expressed, the less important their price sensibility and the more they preferred a comprehensive addendum and credible sources (e.g., government certificate or traceability). The results strongly suggest that advertisers and marketers can customize product communications in order to better engage both the mass market, and ethically oriented consumers.

Humanitarian operational excellence depends on effective coordination and collaboration not only between supply chain partners but also among other actors such as host government, local and international non-government organizations (NGOs), and donors. Importantly, effective coordination and collaboration are facilitated by big data and modern information processing (BDMIP) systems that are complex and interlocked with contemporary information and communication technology (ICT). This study simplifies BDMIP systems by using a comprehensive methodology (literature review and a multicriteria decision-making approach, called the analytic network process) and explores its key determinants and other interconnected factors. The data were collected from humanitarian managers, working in horizontally (e.g., governments, local and international humanitarian organizations) and vertically (e.g.,supply chain partners) collaborated organizations. Three systems (manual, semi-automated, and fully automated) are investigated, which depend on various determinants for operational excellence interlinked with modern big data technology and its components. The results indicate that dynamic compatibility is the most important determinant for such systems to support operational excellence, followed by real-time response, cost, end-to-end visibility, and operational service quality. The implementation of fully automated systems is less cost-effective. This attributes to contemporary dimensions and enablers (e.g. the internet of things, big data collection and analytics, effective data and information sharing, modern unmanned aerial vehicles (called drones), skills for mining structured and unstructured data, among others). Semi-automated systems are also imperative for certain enablers (e.g. data accuracy, data reliability, and personalized data exchange). This study concludes by discussing these findings and their implications for practitioners; how they can combine these technical and operational foundations toexecute humanitarian ...

Humanitarian operational excellence depends on effective coordination and collaboration not only between supply chain partners but also among other actors such as host government, local and international non-government organizations (NGOs), and donors. Importantly, effective coordination and collaboration are facilitated by big data and modern information processing (BDMIP) systems that are complex and interlocked with contemporary information and communication technology (ICT). This study simplifies BDMIP systems by using a comprehensive methodology (literature review and a multicriteria decision-making approach, called the analytic network process) and explores its key determinants and other interconnected factors. The data were collected from humanitarian managers, working in horizontally (e.g., governments, local and international humanitarian organizations) and vertically (e.g., supply chain partners) collaborated organizations. Three systems (manual, semi-automated, and fully automated) are investigated, which depend on various determinants for operational excellence interlinked with modern big data technology and its components. The results indicate that dynamic compatibility is the most important determinant for such systems to support operational excellence, followed by real-time response, cost, end-to-end visibility, and operational service quality. The implementation of fully automated systems is less cost-effective. This attributes to contemporary dimensions and enablers (e.g. the internet of things, big data collection and analytics, effective data and information sharing, modern unmanned aerial vehicles (called drones), skills for mining structured and unstructured data, among others). Semi-automated systems are also imperative for certain enablers (e.g. data accuracy, data reliability, and personalized data exchange). This study concludes by discussing these findings and their implications for practitioners; how they can combine these technical and operational foundations to execute humanitarian ...