An Empirical Model of the Relationships between Manufacturing Capabilities

Item does not contain fulltext***Purpose – The purpose of this paper is to examine the relationships between strategic manufacturing capabilities, particularly whether they are cumulative or trade-off in nature. ***Design/methodology/approach – Uses statistical analyses, particularly structural equation modelling based on data from the third round of the International Manufacturing Strategy Survey. ***Findings – Finds mostly cumulative effects between the strategic capabilities. Shows that “quality” is a basis for “delivery”, which is a basis for “flexibility” and “cost”; between “flexibility” and “cost” an unclear relationship is found. Whether “flexibility” and “cost” are pursued exclusively or simultaneously seems to be connected with the implementation of certain improvement programmes. ***Research limitations/implications – Results cannot be interpreted in a prescriptive way, but only as descriptive findings stemming from a large empirical database. Future research in this area needs to be extended by longitudinal analyses and simulation studies because cross-sectional analyses can only provide indirect empirical measures of dynamic changes of capabilities. ***Practical implications – Describes a common pattern of capability accumulation in the industries investigated. This information can be used to estimate potential competitor behaviour or as a way to perform in an innovative manner. ***Originality/value – Offers a clear conceptualisation of strategic capabilities with the help of an empirical study.28 p

Complexity drivers in manufacturing companies: a literature review

Increasing complexity in manufacturing companies has been one of the biggest issues during the last years. Companies in high-technology marketplaces are confronted with technology innovation, dynamic environmental conditions, changing customer requirements, globalization of markets and competitions as well as market uncertainty. Manufacturing companies can't escape these trends, which induce an increasing amount of complexity. Reasons for this phenomenon are internal and external sources of complexity so-called complexity drivers. Identifying, analyzing and understanding complexity drivers are the first step for complexity management's development and implementation. Complexity management is a strategic issue for companies to be competitive. The purpose of this literature review is to provide a general overview regarding complexity drivers in manufacturing companies. The different definitions of complexity drivers are described, and a new overall definition of complexity drivers is presented. Furthermore, the existing approaches for complexity driver's identification, operationalization and visualization are identified and specified. For complexity driver's clustering, a superior classification system was developed based upon existing classification systems in the literature. The literature review was done by systematically analyzing and collecting existing literature and reveals gaps according to methodology and issue. Existing literature reviews are only focused on specific issues, such as logistics or supply chain management, and do not point out the applied research methodology in detail. A general overview regarding complexity drivers in manufacturing companies and along the value chain does not exist yet