Innovation determinants in manufacturing firms

In this paper the findings of an empirical study concerning the innovation determinants in manufacturing firms is presented. The empirical study covers 184 manufacturing firms located in the Northern Marmara region of Turkey. The types of innovation considered here are product, process, marketing and organizational innovations. An extensive literature survey on innovation determinants is provided. A model is proposed to explore the probable effects and the amount of contribution of the innovation determinants to firm’s innovativeness level. Among all possible determinants considered, intellectual capital has the highest impact on innovativeness followed by organization culture

Determinants of Informal Coordination in Networked Supply Chains

Purpose – Provide insight into the determinants or constructs that enable informally networked supply chains to operate in order to achieve improved operational performance. Design/methodology/approach – The research is based on a wide literature review, focused on the identification of dimensions of informal networking in supply chains along network connectivity, supply chain relationship alignment, informally networked supply chain, and operational performance. These determinants or constructs of informal networking were statistically validated for validity and reliability, using a sample of 231 supply chain professionals. Findings – Four determinant of informal networking were derived: capability connectivity, describing the ability of supply chain partners to rapidly and informally integrate capabilities to service an ad hoc market requirement; relationship alignment or the ability to informally integrate resources across supply chain partners in the context of highly dynamic market situations; the informally networked supply chain itself, measuring the ability of supply chain partners to respond to transient opportunities in the context of highly dynamic markets; and finally operational performance which measures the effect informal networking has on company performance. Research limitations/implications – Future research may investigate the effects of informally networked supply chains on a broader array of measures of company performance, and additional measures of operational performance. Practical implications – These newly developed constructs or determinants give managers further insight into which dimensions need to be fostered to enable informally networked supply chains to operate, and what operational gains may be potentially realised as a result of informal networking. Originality/value – This paper contributes to enhancing the understanding of the newly emerging phenomenon of informal networking in supply chains and how it may yield operational efficiency and effectiveness gains.construct development;coordination;informal networking;supply chain

Make-or-buy configurational approaches in product-service ecosystems and performance

This research examines firm boundary configurations for manufacturers' product-service offerings. We argue that the building of a product-service ecosystem through collaboration with service providers in certain types of business services can increase performance as a result of the superior knowledge-based resources coming from specialized partners. By using fuzzy set qualitative analysis on a sample of 370 multinational manufacturing enterprises (MMNEs), the results reveal that effective servitization is heterogeneous across manufacturing industries and across business service offerings. The findings indicate that most industries achieve their highest performance through collaborations with value-added service providers in two out of three of the service continuum stages (Base and Intermediate services); while keeping the development of Advanced services in-house. The results help to contextualize the best practices for implementing service business models in MMNEs by detailing which service capabilities should be retained in-house and which should be outsourced to specialized partners in various industrial contexts.Peer ReviewedPreprin

Self-resilient production systems : framework for design synthesis of multi-station assembly systems

Product design changes are inevitable in the current trend of time-based competition where product models such as automotive bodies and aircraft fuselages are frequently upgraded and cause assembly process design changes. In recent years, several studies in engineering change management and reconfigurable systems have been conducted to address the challenges of frequent product and process design changes. However, the results of these studies are limited in their applications due to shortcomings in three aspects which are: (i) They rely heavily on past records which might only be a few relevant cases and insufficient to perform a reliable analysis; (ii) They focus mainly on managing design changes in product architecture instead of both product and process architecture; and (iii) They consider design changes at a station-level instead of a multistation level. To address the aforementioned challenges, this thesis proposes three interrelated research areas to simulate the design adjustments of the existing process architecture. These research areas involve: (i) the methodologies to model the existing process architecture design in order to use the developed models as assembly response functions for assessing Key Performance Indices (KPIs); (ii) the KPIs to assess quality, cost, and design complexity of the existing process architecture design which are used when making decisions to change the existing process architecture design; and (iii) the methodology to change the process architecture design to new optimal design solutions at a multi-station level. In the first research area, the methodology in modeling the functional dependence of process variables within the process architecture design are presented as well as the relations from process variables and product architecture design. To understand the engineering change propagation chain among process variables within the process architecture design, a functional dependence model is introduced to represent the design dependency among process variables by cascading relationships from customer requirements, product architecture, process architecture, and design tasks to optimise process variable design. This model is used to estimate the level of process variable design change propagation in the existing process architecture design Next, process yield, cost, and complexity indices are introduced and used as KPIs in this thesis to measure product quality, cost in changing the current process design, and dependency of process variables (i.e, change propagation), respectively. The process yield and complexity indices are obtained by using the Stream-of-Variation (SOVA) model and functional dependence model, respectively. The costing KPI is obtained by determining the cost in optimizing tolerances of process variables. The implication of the costing KPI on the overall cost in changing process architecture design is also discussed. These three comprehensive indices are used to support decision-making when redesigning the existing process architecture. Finally, the framework driven by functional optimisation is proposed to adjust the existing process architecture to meet the engineering change requirements. The framework provides a platform to integrate and analyze several individual design synthesis tasks which are necessary to optimise the multi-stage assembly processes such as tolerance of process variables, fixture layouts, or part-to-part joints. The developed framework based on transversal of hypergraph and task connectivity matrix which lead to the optimal sequence of these design tasks. In order to enhance visibility on the dependencies and hierarchy of design tasks, Design Structure Matrix and Task Flow Chain are also adopted. Three scenarios of engineering changes in industrial automotive design are used to illustrate the application of the proposed redesign methodology. The thesis concludes that it is not necessary to optimise all functional designs of process variables to accommodate the engineering changes. The selection of only relevant functional designs is sufficient, but the design optimisation of the process variables has to be conducted at the system level with consideration of dependency between selected functional designs

Differences between European Regional Innovation Systems in Terms of Technological and Economic Characteristics

innovation, networks

Modeling and Optimization of Stochastic Process Parameters in Complex Engineering Systems

For quality engineering researchers and practitioners, a wide number of statistical tools and techniques are available for use in the manufacturing industry. The objective or goal in applying these tools has always been to improve or optimize a product or process in terms of efficiency, production cost, or product quality. While tremendous progress has been made in the design of quality optimization models, there remains a significant gap between existing research and the needs of the industrial community. Contemporary manufacturing processes are inherently more complex - they may involve multiple stages of production or require the assessment of multiple quality characteristics. New and emerging fields, such as nanoelectronics and molecular biometrics, demand increased degrees of precision and estimation, that which is not attainable with current tools and measures. And since most researchers will focus on a specific type of characteristic or a given set of conditions, there are many critical industrial processes for which models are not applicable. Thus, the objective of this research is to improve existing techniques by not only expanding their range of applicability, but also their ability to more realistically model a given process. Several quality models are proposed that seek greater precision in the estimation of the process parameters and the removal of assumptions that limit their breadth and scope. An extension is made to examine the effectiveness of these models in both non-standard conditions and in areas that have not been previously investigated. Upon the completion of an in-depth literature review, various quality models are proposed, and numerical examples are used to validate the use of these methodologies

The Link between Environmental Innovation, Patents, and Environmental Management

This paper analyses empirically the relationship between environmental innovations, environmental management and patenting. In particular it tests a number of propositions on how environmental management systems and the interaction with environmentally more or less concerned stakeholders are associated with the probability of firms to pursue innovation in general (measured as patenting behaviour) and specifically environmental innovation (measured as firm self-assessment and based on patent data). In applying a negative binomial as well as binary discrete choice models the relationship is studied using data on German manufacturing firms. As a novel and important insight, the study finds that environmental innovation can be meaningfully identified using patent data and that environmental innovation defined this way is less ubiquitous than self-reported environmental innovation. It also reveals that the implementation level of environmental management systems has a positive effect exclusively on environmental process innovation, whereas it is negatively associated with the level of a firm’s general patenting activities. For environmental product innovation and patented environmental innovations a positive relationship with environ-mentally concerned and a negative link with environmentally neutral stakeholders is found.Environmental innovations, patents