Reference model for implementing an MRP system in a highly diverse component and seasonal lean production environment

Companies are currently choosing to integrate logics and systems to achieve better solutions. These combinations also include companies striving to join the logic of material requirement planning (MRP) system with the systems of lean production. The purpose of this article was to design an MRP as part of the implementation of an enterprise resource planning (ERP) in a company that produces agricultural implements, which has used the lean production system since 1998. This proposal is based on the innovation theory, theory networks, lean production systems, ERP systems and the hybrid production systems, which use both components and MRP systems, as concepts of lean production systems. The analytical approach of innovation networks enables verification of the links and relationships among the companies and departments of the same corporation. The analysis begins with the MRP implementation project carried out in a Brazilian metallurgical company and follows through the operationalisation of the MRP project, until its production stabilisation. The main point is that the MRP system should help the company's operations with regard to its effective agility to respond in time to demand fluctuations, facilitating the creation process and controlling the branch offices in other countries that use components produced in the matrix, hence ensuring more accurate estimates of stockpiles. Consequently, it presents the enterprise knowledge development organisational modelling methodology in order to represent further models (goals, actors and resources, business rules, business process and concepts) that should be included in this MRP implementation process for the new configuration of the production system.     

Emergence of shared leadership networks in teams: An adaptive process perspective

Adaptive leadership theory suggests that shared leadership networks grow in a complex manner. We propose that leadership decentralization (the dispersion of leadership), leadership density (the total amount of leadership), and situationally-aligned leadership (SAL: leadership transitions to those who fit situation requirements) are distinct aspects of a shared leadership network and should be examined together to capture the development of shared leadership process. Through a study of 450 participants in 90 teams, we find that each of these three aspects of shared leadership plays a different role during shared leadership network emergence. Specifically, transactive memory systems (TMS) contribute to decentralized leadership structures, which in turn precipitate more dense leadership networks. We also find that TMS contributes to the most situationally aligned team member engaging in leadership. Both leadership density and SAL predict team performance. We discuss the theoretical and practical implications of these results.     

Performativity as ongoing journeys: Implications for strategy,entrepreneurship, and innovation

For the most part, strategy, entrepreneurship, and innovation have been researched and practiced from a representational position. In this paper, we make a case for taking a performative turn. Strategists, entrepreneurs, and intrapreneurs are embedded-embodied actors who engage in material-discursive practices in their attempts at constituting phenomena. Overflows, which are inevitable given dispersion of agency, give rise to matters of concern for multiple stakeholder groups. Settlements between stakeholders are temporary, as phenomena will be de-constituted when constitutive arrangements change. Consequently, the projects and initiatives that strategists, entrepreneurs, and intrapreneurs undertake are best seen as ongoing journeys.     

Developing new innovation models: Shifts in the innovation landscapes in emerging economies and implications for global R&D management

Over the past two decades, there has been a substantial shift in the global innovation landscape. Multinationals from developed economies are increasingly globalizing their R&D activities and are developing an “open innovation” model to source innovations from outside the firm, including from emerging economies such as those in Asia. In addition, emerging economy firms, which traditionally have played a secondary role in the global innovation landscape, have now begun to catch up in developing their own innovative capabilities. This study explores the implications of this new innovation landscape for CEOs of multinationals and emerging economy firms, as well as for international management scholars and educators. While the multinationals might appropriate rents from their existing capabilities and source new ones in emerging economies, they may be threatened by weak intellectual property rights regimes and unintended knowledge spillovers to local firms, creating potential competitors. Firms in the emerging economies can learn from and catch up with investing multinationals, but to do so they need to develop their own innovative capabilities and move from a process to a product focus and from imitation to innovation.     

A comparison of Japanese failure models: Hybrid neural networks,logit models,and discriminant analysis

This article looks at the ability of a relatively new technique, hybrid artificial neural networks (ANNs), to predict Japanese banking and firm failures. These models are compared with traditional statistical techniques and conventional ANN models. The results suggest that hybrid neural networks outperform all other models in predicting failure for one year prior to the event. This suggests that for researchers, policymakers, and others interested in early warning systems, the hybrid network may be a useful tool for predicting banking and firm failures.     

Designing interorganizational networks for innovation: An empirical examination of network configuration, formation and governance

Strategic SME networks have received significant policy attention, yet a review of the current literature reveals limited attention to the factors that contribute to network innovation. This study examines the influence of the number of member firms (network size), the extent to which a network is based on firm incentives (bottom-up formation), and the extent of development of the governance structure (size of administrative function) on a network's innovative performance. Latent growth modeling with longitudinal data from 53 networks reveals that larger networks and bottom-up formed networks achieve greater innovative performance, and that the administrative function partially mediates these effects.     

OMEGa: an optimistic most energy gain method for minimum energy multicasting in wireless ad hoc networks

In wireless ad hoc networks where every device runs on its own battery, the energy consumption is critical to lengthen the network lifetime. The communication among devices in the network can be categorized as unicasting and multicasting (including broadcasting). For the case of unicasting, computing the energy optimal path between the two communicating nodes is polynomially solvable by computing the shortest path. But for the case of multicasting, shortest path or minimum spanning tree does not guarantee an energy optimal communication. In this paper, we present our novel approach, Optimistic Most Energy Gain (OMEGa) method, for the minimum energy multicasting in wireless ad hoc networks. OMEGa aims at maximum utilization of Wireless Multicast Advantage (WMA), which essentially means covering more nodes by using larger energy. Both theoretical and experimental analysis shows OMEGa method performs very well. Research is partially supported by NSF and Air Force grants.