@article{KellnerUtz2024, author = {Kellner, Florian and Utz, Sebastian}, title = {An inverse optimization approach for studying sustainability preferences in sourcing decisions}, series = {Journal of Cleaner Production}, volume = {483}, journal = {Journal of Cleaner Production}, doi = {10.1016/j.jclepro.2024.144305}, year = {2024}, abstract = {Throughout many societies around the globe, there is growing awareness of the urgent need for the transition towards a sustainable economy. Research shows that buying firms have substantial leverage to initiate sustainable development by controlling the sustainable performance of their suppliers. In that context, this article presents a novel methodology based on inverse optimization to derive the implicit preferences of decision-makers in the trade-off between traditional sourcing objectives and sustainability in the supplier selection and order allocation process. The derived implicit preferences can then be used for further analyses to gain a better understanding of the characteristics of purchasing managers and sourcing situations that come with particularly high/low preferences placed on sustainability. Since the inverse optimization approach is computationally resource-intensive and consumes a significant amount of time, we present a scalable state-of-the-art cloud architecture that allows solving an arbitrary number of optimization programs in an acceptable amount of time. We demonstrate the feasibility of the proposed methodology in a real-world case. In doing so, we test how important sustainability aspects are in the supplier selection and order allocation decisions of one of the world's largest automotive parts manufacturers.}, language = {en} } @article{NeumuellerLaschKellner2016, author = {Neum{\"u}ller, Claudia and Lasch, Rainer and Kellner, Florian}, title = {Integrating sustainability into strategic supplier portfolio selection}, series = {Management Decision}, volume = {54}, journal = {Management Decision}, number = {1}, doi = {10.1108/MD-05-2015-0191}, pages = {194 -- 221}, year = {2016}, abstract = {Purpose The purpose of this paper is to propose a comprehensive methodology and a problem-specific model for the configuration of the optimal strategic supplier portfolio in terms of traditional, performance-related objectives and sustainability targets. Design/methodology/approach To bridge the research gap, i.e., to align strategic supplier portfolio selection with corporate sustainability targets, a hybrid model of the analytic network process (ANP) and goal programming (GP) is developed. To validate the model, a case example is presented and managerial feedback is collected. Findings By enabling the integration of sustainability targets into strategic supplier portfolio configuration, the hybrid ANP-GP model contributes to research in the area of sustainable supply chain management. Results indicate that simplifying the model by omitting one or more details may lead to unfortunate actions. Research limitations/implications The model has been applied using a case example in the automotive industry. To strengthen the findings, it should be examined under other terms as well. Practical implications Integrating economic, environmental, and social targets into strategic supplier portfolio configuration reduces supply risks and promotes the achievement of the sustainability goals of the purchasing company. Social implications Strategic supplier selection counts among the decisions that have an impact on the environment and society for several years. Configuring economically rational, environmentally friendly, and socially responsible supplier bases supports worldwide efforts towards sustainable development. Originality/value Although sustainable supplier selection has gained importance in recent years, this is the first time that a comprehensive model for the determination of the optimal strategic supplier portfolio in terms of performance-related objectives and sustainability targets has been proposed.}, language = {en} } @article{KellnerUtz2019, author = {Kellner, Florian and Utz, Sebastian}, title = {Sustainability in supplier selection and order allocation: combining integer variables with Markowitz portfolio theory}, series = {Journal of Cleaner Production}, volume = {214}, journal = {Journal of Cleaner Production}, doi = {10.1016/j.jclepro.2018.12.315}, pages = {462 -- 474}, year = {2019}, abstract = {This research presents a decision support methodology for the multi-criteria supplier selection and order allocation problem. The proposed approach supports purchasing managers in assembling mid-term supplier portfolios while making them aware of the trade-offs between the supplier sustainability, the purchasing costs, and the overall supply risk. First, we propose a multi-objective optimization model with three objectives: to maximize the supplier sustainability, to select the supplier portfolio with the lowest purchasing costs, and to minimize the supply risk. Our model extends existing mathematical approaches that follow the portfolio theory fathered by H. Markowitz by integrating the aspect 'risk' into the supplier selection problem. Secondly, since we allow for integer variables in our model—in contrast to the classical Markowitz portfolio theory—we use the ε-constraint method to visualize the efficient surface. The possibility of considering the non-dominated set of supplier portfolios is advantageous for purchasing managers as they gain a picture of the different optimal supplier portfolios and are able to analyze the trade-offs between the different purchasing goals before making a decision. Finally, we illustrate the applicability of the proposed methodology in a real-world supplier selection and order allocation case from the automotive industry. In the example case, we identify 1754 optimal supplier portfolios that may be assembled based on the eight available suppliers. Our analyses show that each optimal portfolio consists of two suppliers, with one specific supplier being included in each portfolio. Furthermore, four suppliers are not part of any optimal solution.}, language = {en} }