Production systems and supplier selection: a multi-phase process model

Purpose: This paper presents a combined multi-phase supplier selection model. The process repeatedly revisits the criteria and sourcing decision as the development process continues. This enables a structured adoption of product and production system innovation from strategic suppliers, where previously the literature purely focuses on product innovation or cost reduction. Design/methodology/approach: The authors adopted an embedded researcher style, inductive, qualitative case study of an industrial supply cluster comprising a focal automotive company and its interaction with three different strategic stamping suppliers. Findings: Our contribution is the multi-phased production and product innovation process. This is an advance from traditional supplier selection and also an extension of ideas of supplier-located product development as it includes production system development, and complements the literature on working with strategic suppliers. Specifically, we explicitly articulate the previously unreported issue of whether a supplier chosen for its innovation capabilities at the start of the new product development process will also be the most appropriate supplier during the production system development phase, when an ability to work collaboratively may be the most important attribute, or in the large-scale production phase when an ability to manufacture at low unit cost may be most important. Originality/value: The paper identifies a multi-phase approach to tendering within a fixed body of strategic suppliers which seeks to identify the optimum technological and process decisions as well as the traditional supplier sourcing choice. These areas have not been combined before and generate a valuable approach for firms to adopt as well as for researchers to extend our understanding of a highly complex process.

An algebra and conceptual model for semantic tagging of collaborative digital libraries

Cost-effective semantic description and annotation of shared knowledge resources has always been of great importance for digital libraries and large scale information systems in general. With the emergence of the Social Web and Web 2.0 technologies, a more effective semantic description and annotation, e.g., folksonomies, of digital library contents is envisioned to take place in collaborative and personalised environments. However, there is a lack of foundation and mathematical rigour for coping with contextualised management and retrieval of semantic annotations throughout their evolution as well as diversity in users and user communities. In this paper, we propose an ontological foundation for semantic annotations of digital libraries in terms of flexonomies. The proposed theoretical model relies on a high dimensional space with algebraic operators for contextualised access of semantic tags and annotations. The set of the proposed algebraic operators, however, is an adaptation of the set theoretic operators selection, projection, difference, intersection, union in database theory. To this extent, the proposed model is meant to lay the ontological foundation for a Digital Library 2.0 project in terms of geometric spaces rather than logic (description) based formalisms as a more efficient and scalable solution to the semantic annotation problem in large scale.

Partner selection in green supply chains using PSO - a practical approach

Partner selection is crucial to green supply chain management as the focal firm is responsible for the environmental performance of the whole supply chain. The construction of appropriate selection criteria is an essential, but often neglected pre-requisite in the partner selection process. This paper proposes a three-stage model that combines Dempster-Shafer belief acceptability theory and particle swarm optimization technique for the first time in this application. This enables optimization of both effectiveness, in its consideration of the inter-dependence of a broad range of quantitative and qualitative selection criteria, and efficiency in its use of scarce resources during the criteria construction process to be achieved simultaneously. This also enables both operational and strategic attributes can be selected at different levels of hierarchy criteria in different decision-making environments. The practical efficacy of the model is demonstrated by an application in Company ABC, a large Chinese electronic equipment and instrument manufacturer.

Partner selection for reverse logistics centres in green supply chains: a fuzzy artificial immune optimization approach

The design of reverse logistics networks has now emerged as a major issue for manufacturers, not only in developed countries where legislation and societal pressures are strong, but also in developing countries where the adoption of reverse logistics practices may offer a competitive advantage. This paper presents a new model for partner selection for reverse logistic centres in green supply chains. The model offers three advantages. Firstly, it enables economic, environment, and social factors to be considered simultaneously. Secondly, by integrating fuzzy set theory and artificial immune optimization technology, it enables both quantitative and qualitative criteria to be considered simultaneously throughout the whole decision-making process. Thirdly, it extends the flat criteria structure for partner selection evaluation for reverse logistics centres to the more suitable hierarchy structure. The applicability of the model is demonstrated by means of an empirical application based on data from a Chinese electronic equipment and instruments manufacturing company.

Reputation performance: a portfolio selection approach

This paper introduces a normative view on corporate reputation strategic management. Reputation performance is conceptualised as the outcome of complex processes and social interactions and the lack of a holistic reputation performance management framework is identified. In an attempt to fill this gap, a portfolio-based approach is put forward. Drawing on the foundations of modern portfolio theory we create a portfolio-based reputation management algorithmic model where reputation components and priorities are weighted by decision makers and shape organisational change in an attempt to formulate a corporate reputation strategy. The rationale of this paper is based on the foundational consideration of organisations as choosing he optimal strategy by seeking to maximise their reputation performance while maintaining organisational stability and minimising organisational risk.

Understanding how sporting characteristics and behaviours influence destination selection: a grounded theory study of golf tourism

Sports tourism has received growing attention in academic research over the past two decades (Weed and Bull, 2009, Gibson, 2005) but greater understanding of the consumer is needed, particularly the factors influencing decisions to include sport as part of a leisure trip. This paper provides, through a focus on the sport of golf, insight into the characteristics of the sports tourist and how sports tourist behaviours influence the selection of locations deemed suitable for sports participation. This qualitative research employs a grounded theory methodology, underpinned by a constructivist epistemology, to evaluate twenty-six in-depth interviews with golf tourists. The findings propose a model which explains the relationship between golf tourist behaviours and destination selection. This identifies six strands which determine the relationship between the golf tourist, golf behaviours and destination selection (constructing the golf holiday, emotional rewards of taking a trip, total trip spend, amenities and support facilities, course characteristics and reputation of the destination). Furthermore it illuminates the complexity of these relationships through recognition of four spheres of influence (group dynamics, competition and ability, golfing capital and intermediaries). Discussion elucidates how this increased understanding of the golf tourist behaviours and destination selection might be applied to other sports, with conclusions exploring implications for the sports tourism industry and destinations.

Reputation Performance: a portfolio selection approach

This paper introduces a normative view on corporate reputation management; an algorithmic model for reputation-driven strategic decision making is proposed and corporate reputation is conceptualized as influenced by a selection among organizational priorities. A portfolio-based approach is put forward; we draw on the foundations of portfolio theory and we create a portfolio-based reputation management model where reputation components and priorities are weighted by decision makers and shape organizational change in an attempt to formulate a corporate reputation strategy. The rationale of this paper is based on the foundational consideration of organizations as choosing the optimal strategy by seeking to maximize performance on corporate reputation capital while maintaining organizational stability and minimizing organizational risk.