25,613 research outputs found

    INFORMATION TECHNOLOGY AND THE VERTICAL ORGANIZATION OF INDUSTRY

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    A model has been developed to study the interdependence between the choice of information technology and industry structure. Advances in information technology might provide incentives for a firm to specialize or focus on its core competence. However, the degree of specialization depends on the extent of industry-level specialization, which is, in turn, the result of the behavior of individual firms and their adoption of information technology favoring specialization. Emerging electronic markets and industries have been chosen as an application domain, as they would not exist without information technology.

    Electronic Reverse Auctions: Spawning Procurement Innovation in the Context of Arab Culture

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    Government e-procurement initiatives have the potential to transform local institutions, but few studies have been published of strategies for implementing specific e-procurement tools, particularly involving procurement by a foreign government adapting to local culture in the Middle East/North Africa (MENA). This case describes procurement at a forward operating base (FOB) in Kuwait in support of operations in Iraq. The government procurers had to deal with a phenomenon unique to the MENA region: wasta. Wasta is a form of social capital that bestows power, influence, and connection to those who possess it, similar to guanxi in China. This study explores the value proposition and limitations of electronic reverse auctions (eRA) with the purpose of sharing best practices and lessons learned for government procurement in a MENA country. The public value framework provides valuable theoretical insights for the implementation of a new government e-procurement tool in a foreign country. In a culture dominated by wasta, the suppliers enjoyed the transparency and merit-based virtues of eRA’s that transferred successfully into the new cultural milieu: potential to increase transparency, competition, efficiency, and taxpayer savings. The practices provided herein are designed specifically to help buyers overcome structural barriers including training, organizational inertia, and a lack of eRA policy and guidance while implementing a new e-procurement tool in a foreign country

    Learner course recommendation in e-learning based on swarm intelligence

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    Se dan unas recomendaciones en la enseñanza asistida por ordenador (e-learning) basada en la inteligencia colectiva.This paper analyses aspects about the recommendation process in distributedinformation systems. It extracts similarities and differences between recommendations in estores and the recommendations applied to an e-learning environment. It also explains the phenomena of self-organization and cooperative emergence in complex systems coupled with bio-inspired algorithms to improve knowledge discovery and association rules. Finally, the present recommendation is applied to e-learning by proposing recommendation by emergence in a multi.agent system architecture

    Enhancing the Supply Chain Performance by Integrating Simulated and Physical Agents into Organizational Information Systems

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    As the business environment gets more complicated, organizations must be able to respond to the business changes and adjust themselves quickly to gain their competitive advantages. This study proposes an integrated agent system, called SPA, which coordinates simulated and physical agents to provide an efficient way for organizations to meet the challenges in managing supply chains. In the integrated framework, physical agents coordinate with inter-organizations\' physical agents to form workable business processes and detect the variations occurring in the outside world, whereas simulated agents model and analyze the what-if scenarios to support physical agents in making decisions. This study uses a supply chain that produces digital still cameras as an example to demonstrate how the SPA works. In this example, individual information systems of the involved companies equip with the SPA and the entire supply chain is modeled as a hierarchical object oriented Petri nets. The SPA here applies the modified AGNES data clustering technique and the moving average approach to help each firm generalize customers\' past demand patterns and forecast their future demands. The amplitude of forecasting errors caused by bullwhip effects is used as a metric to evaluate the degree that the SPA affects the supply chain performance. The experimental results show that the SPA benefits the entire supply chain by reducing the bullwhip effects and forecasting errors in a dynamic environment.Supply Chain Performance Enhancement; Bullwhip Effects; Simulated Agents; Physical Agents; Dynamic Customer Demand Pattern Discovery

    Intelligent Agent Based Approach to Sales Operations at eStores

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    In our paper, we consider the application of Intelligent Agents in supporting the operations in an Internet-based store (estore). We consider and discuss different opportunities for employing Intelligent Agents to improve the performance of an estore\u27s operations, including sales, forecasting demand and supporting order fulfillment. We provide a framework for the application of such agents, show available sources of information, and discuss challenging issues in modeling learning and decision processes for agents

    Shopping with Voice Assistants: How Empathy Affects Individual and Family Decision-Making Outcomes

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    Artificial intelligence (AI)-enabled voice assistants (VAs) such as Amazon Alexa increasingly assist shopping decisions and exhibit empathic behavior. The advancement of empathic AI raises concerns about machines nudging consumers into purchasing undesired or unnecessary products. Yet, it is unclear how the machine’s empathic behavior affects consumer responses and decision-making outcomes during voice-enabled shopping. This article draws from the service robot acceptance model (sRAM) and social response theory (SRT) and presents an individual-session experiment where families (vs. individuals) complete actual shopping tasks using an ad-hoc Alexa app featuring high (vs. standard) empathic capabilities. We apply the experimental conditions as moderators to the structural model, bridging selected functional, social-emotional, and relational variables. Our framework collocates affective empathy, explicates the bases of consumers’ beliefs, and predicts behavioral outcomes. Findings demonstrate (i) an increase in consumers’ perceptions, beliefs, and adoption intentions with empathic Alexa, (ii) a positive response to empathic Alexa holding constant in family settings, and (iii) an interaction effect only on the functional model dimensions whereby families show greater responses to empathic Alexa while individuals to standard Alexa
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