Abstract

Abstract

Abstract
Purpose - The purpose of this paper is to study the alignment measurement in collaborative networks, using the fit concept and predictive performance measurement as its main enablers. A performance prediction approach is used in order to control a collaborative business network based not only in present and past performance measurements of each partner, but also taking into account the future behaviour of the intra- and inter-organisational processes performance. Design/methodology/approach - An exploratory case study was applied to a Brazilian collaborative network and mathematical approaches normally used in control theory were adopted to support alignment measurement. Findings - The use of predictive measurements to manage the alignment between the results of inter-organisational processes and performance targets set by the collaborative network. Research limitations/implications - This approach was applied in a specific supply chain network, based on three industrial companies. For other network typologies it will be necessary to evaluate the alignment that can be achieved. Practical implications - This predictive approach makes it possible to manage performance pro-actively using feedforward and feedback control. Therefore, tools that consider performance estimation are used based on a data fusion approach, with a proper combination of leading and lagging measurements, which make it possible to use forecasting methods and tools to achieve good predictions. Originality/value - The paper introduces an approach to alignment measurement leveraged by the new paradigm of performance prediction and presents an alignment metric for collaborative networks. © Emerald Group Publishing Limited.

Abstract
Purpose - Customer experience has become increasingly important for service organizations that see it as a source of sustainable competitive advantage, and for service designers, who consider it fundamental to any service design project. Design/methodology/approach - Integrating contributions from different fields, CEM was conceptually developed to represent the different aspects of customer experience in a holistic diagrammatic representation. CEM was further developed with an application to a multimedia service. To further develop and build CEM's models, 17 customers of a multimedia service provider were interviewed and the data were analyzed using Grounded Theory methodology. Findings - Combining multidisciplinary contributions to represent customer experience elements enables the systematization of its complex information. The application to a multimedia service highlights how CEM can facilitate the work of multidisciplinary design teams by providing more insightful inputs to service design. Originality/value - CEM supports the holistic nature of customer experience, providing a systematic portrayal of its context and shifting the focus from single experience elements to their orchestration.

Abstract
Driven by a real-world application in the beverage industry, this paper provides a design of a new VNS variant to tackle the annual production budget problem. The problem consists of assigning and scheduling production lots in a multi-plant environment, where each plant has a set of filling lines that bottle and pack drinks. Plans also consider final product transfers between the plants. Our algorithm fixes setup variables for family of products and determines production, inventory and transfer decisions by solving a linear programming (LP) model. As we are dealing with very large problem instances, it is inefficient and unpractical to search the entire neighborhood of the incumbent solution at each iteration of the algorithm. We explore the sensitivity analysis of the LP to guide the partial neighborhood search. Dual-reoptimization is also used to speed-up the solution procedure. Tests with instances from our case study have shown that the algorithm can substantially improve the current business practice, and it is more competitive than state-of-the-art commercial solvers and other VNS variants.

Abstract
In this paper, we propose three novel mathematical models for the two-stage lot-sizing and scheduling problems present in many process industries. The problem shares a continuous or quasi-continuous production feature upstream and a discrete manufacturing feature downstream, which must be synchronized. Different time-based scale representations are discussed. The first formulation encompasses a discrete-time representation. The second one is a hybrid continuous-discrete model. The last formulation is based on a continuous-time model representation. Computational tests with state-of-the-art MIP solver show that the discrete-time representation provides better feasible solutions in short running time. On the other hand, the hybrid model achieves better solutions for longer computational times and was able to prove optimality more often. The continuous-type model is the most flexible of the three for incorporating additional operational requirements, at a cost of having the worst computational performance. Journal of the Operational Research Society (2012) 63, 1613-1630. doi:10.1057/jors.2011.159 published online 7 March 2012