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Exploring the academic-industry collaboration in knowledge sharing for supplier selection : digitalizing the OEM
Get PDFIncreasing reliance on digital technologies has led to a significant shift in how businesses operate, with many now relying heavily on digital platforms for effective planning, communication, sales, marketing, supply chain, and logistics management. In this context, knowledge sharing platforms enable academic-industry collaboration in which exchange of ideas, opinions, experience, and expertise brings collective intelligence in cooperative learning ecosystem thereby expediting decision making. However, establishing long-term commitment among the partners, allocation of time and resources for sharing tacit knowledge, collaboration among partners with different strategic priorities, and real-time knowledge sharing capabilities are essential for effective and rapid learning in knowledge sharing platforms. The present article will examine these benefits and challenges in knowledge sharing and its impact on supplier selection platforms in Asian automakers. The findings of this article will be helpful for researchers and practitioners intending to explore the role of cooperation in knowledge sharing and digital transformation amid competitive environment prevalent in the automotive industry. The potential supplier database is first examined for qualifying the capability requirements put forth in this article and further prioritized using a multicriteria decision-making technique and analytic hierarchy process. The article results reveal that the manufacturer has highly prioritized firms' financial transparency for supplier evaluation followed by the suppliers' cost control, quality control, and manufacturing capabilities. The article has significant theoretical and practical implications for developing robust supplier evaluation criteria for automobile industry and a digital ecosystem for original equipment manufacturers in making supplier related decisions. © 1988-2012 IEEE
Religion and relationality in punk : musicking and ordinary ethics
No full textEngaging with Christopher Small's notion of musicking and Veena Das and Michael Lambek's notion of ordinary ethics, this article analyzes research on religion in punk from religion studies, sociology, and theology to offer a (self) critique of the representation of religious belief and relationships in punk. Focusing on the presence of evangelical Christianity in contemporary punk, and emphasizing relationships as central to the activity of musicking, this article draws attention to exclusions and essentializations in research in this field. Focusing on the ordinary ethics enacted through punk musicking, rather than the normative ethics located in sometimes polemical punk statements and scholarship, it is argued that a more accurate understanding of the place of religion in punk becomes apparent by focusing on quotidian relational practices. © University of Toronto Press, 2024
Focus on education : taking stock of key themes, topics, trends and communities in international business and international management education research
Get PDFThis paper sheds light on education in International Business (IB) and International Management (IM) by identifying the main topics, themes, trends and subdomain clusters in their education-focused literature. Using a combination of text- and network-based analysis, only recently introduced for data analysis in IB/IM, we reveal themes focused mainly on five areas: global focus; learning and skill development; teaching and curriculum development; economic and management issues; and student types and experience. Further, we examine the extent to which keywords associated with critical perspectives enter the education literature to gain insight into the embrace of issues related to sustainability, ethics, empathy and gender. © 2023 The Author
The negative Commonwealth : Australia as ‘laboratory’, then and now
No full textFederated Australia was seen for a long time as a significant social ‘laboratory’. The Commonwealth itself was seen as an ‘experiment’. This widespread metaphor relied on a particular pattern of perception: the country was ‘new’ (it was not), and the country was allegedly isolated (it was not, at least not completely). Many believed that its social environment could be controlled, like that of a scientific laboratory. A laboratory is designed to shut all disturbances out – the value of the data and experiments depends on it. This article outlines this metaphor in the context of Australian history during the 20th century, its rhetorical power and what made it discursively possible. © The Author(s) 2024
An improved congestion-controlled routing protocol for IoT applications in extreme environments
No full textThe Internet of Things (IoT) has shown its presence in applications that require monitoring extreme environments, such as wildfires, military operations, and coastal areas, among others. In these applications, the IoT nodes are deployed in hazardous terrains where humanistic access is hard or not possible. Hence, to ensure reliable data transmission in these applications, novel routing protocols need to be designed due to the multihop nature of communication possessed by the deployed nodes. Currently, most of the routing protocols utilized by IoT nodes follow traditional approaches, which creates congestion and contention in the network. As a result, the network performance is degraded in terms of various communication metrics. To address this problem and improve the communication statistics in extreme environments, we propose a deep- Q -learning-enable-destination-sequenced distance-vector (DQL-DSDV) framework. DQL-DSDV focuses on selecting the next hop during communication. Initially, the DSDV protocol updates routing information for connected nodes. This information is subsequently utilized by the deep- Q -learning (DQL) algorithm to compute the next hop count. This computation is based on reward functions, known as Q-values, which are conceptualized as the distance between connected nodes by taking into account the traffic flow. These distinguishing operational features of DQL and DSDV ensure that DQL-DSDV minimizes the packet lost ratio, congestion, end-to-end delay, and communication cost with improved Quality of Service (QoS). During simulations, we observed significant improvement in these performance metrics, in the presence of the existing schemes. Despite that, we checked the computation complexity of the proposed approach with existing protocols, which demonstrated noteworthy outcomes just like the other metrics. © 2014 IEEE
Implementing Lean Six Sigma in financial services: the effect of motivations, selected methods and challenges on LSS program- and organizational performance
Get PDFPurpose: The purpose of this paper is to contribute to the limited body of empirical knowledge on the impact of Lean Six Sigma (LSS) program implementations on organizational performance in financial services by investigating how antecedents of Lean Six Sigma program success (motivations, selected LSS methods and challenges) affect organizational performance enhancement via LSS program performance. Design/methodology/approach: A sample of 198 LSS professionals from 7 countries are surveyed. Structural equation modeling (SEM) is performed to test the questioned relations. Findings: This study’s findings comprise: (1) LSS program performance partially mediates the relationship between motivations for LSS implementation and organizational performance, (2) selected LSS method applications has a fully (mediated) indirect impact on organizational performance, (3) LSS implementation challenges also have an indirect (mediated) impact on organizational performance and (4) LSS program performance has a positive impact on organizational performance. Originality/value: The findings of this research predominantly provide nuances and details about LSS implementation antecedents and effects, useful for managers in advising their business leaders about the prerequisites and potential operational and financial benefits of LSS implementation. Furthermore, the paper provides evidence and details about the relationship between important antecedents for LSS implementation identified in existing literature and their impact on organizational performance in services. Thereby, this research is the first in providing empirical, cross-sectional, evidence for the antecedents and effects of LSS program implementations in financial services. © 2023, Abhishek Vashishth, Bart Alex Lameijer, Ayon Chakraborty, Jiju Antony and Jürgen Moormann
Predictors of life satisfaction : a nationwide investigation in Iran
Get PDFIran is a developing country with low levels of economic development and globalization and is ruled by a theocratic government. To address the lack of national research on well-being in Iran, this retrospective observational study aims to examine life satisfaction and its main determinants among Iranian adults. Using World Gallup Poll data collected between 2006 and 2017, we examined life satisfaction as a cognitive aspect of subjective well-being in relation to various factors. Our results show that income is the strongest predictor of life satisfaction, followed by standard of living, gender, social support, age, negative affect, and education. In developing countries such as Iran, which face significant economic, political, and social challenges, individuals prioritize the satisfaction of basic needs by emphasizing factors such as the socioeconomic status. In contrast, developed countries with established welfare systems may emphasize other values such as social connections and healthy lifestyle behaviors as key factors in life satisfaction. This study contributes to a deeper understanding of the determinants of life satisfaction in Iran and provides insights for future research and policy making. © 2024 Nasim Salehi et al
Fuzzy multiplier, sum and intersection rules in non-Lipschitzian settings : decoupling approach revisited
Get PDFWe revisit the decoupling approach widely used (often intuitively) in nonlinear analysis and optimization and initially formalized about a quarter of a century ago by Borwein & Zhu, Borwein & Ioffe and Lassonde. It allows one to streamline proofs of necessary optimality conditions and calculus relations, unify and simplify the respective statements, clarify and in many cases weaken the assumptions. In this paper we study weaker concepts of quasiuniform infimum, quasiuniform lower semicontinuity and quasiuniform minimum, putting them into the context of the general theory developed by the aforementioned authors. Along the way, we unify the terminology and notation and fill in some gaps in the general theory. We establish rather general primal and dual necessary conditions characterizing quasiunifor
DQN approach for adaptive self-healing of VNFs in cloud-native network
Get PDFThe transformation from physical network function to Virtual Network Function (VNF) requires a fundamental design change in how applications and services are tested and assured in a hybrid virtual network. Once the VNFs are onboarded in a cloud network infrastructure, operators need to test VNFs in real-time at the time of instantiation automatically. This paper explicitly analyses the problem of adaptive self-healing of a Virtual Machine (VM) allocated by the VNF with the Deep Reinforcement Learning (DRL) approach. The DRL-based big data collection and analytics engine performs aggregation to probe and analyze data for troubleshooting and performance management. This engine helps to determine corrective actions (self-healing), such as scaling or migrating VNFs. Hence, we proposed a Deep Queue Learning (DQL) based Deep Queue Networks (DQN) mechanism for self-healing VNFs in the virtualized infrastructure manager. Virtual network probes of closed-loop orchestration perform the automation of the VNF and provide analytics for real-time, policy-driven orchestration in an open networking automation platform through the stochastic gradient descent method for VNF service assurance and network reliability. The proposed DQN/DDQN mechanism optimizes the price and lowers the cost by 18% for resource usage without disrupting the Quality of Service (QoS) provided by the VNF. The outcome of adaptive self-healing of the VNFs enhances the computational performance by 27% compared to other state-of-the-art algorithms. © 2013 IEEE
