Configurators have the potential to revolutionize the business processes of Engineering-to-order (ETO) companies. Despite their positive impacts on ETO companies' operations and strategies, there is ...a paucity of empirical investigations examining the development processes and practices of configurators, in particular integrated configurators. We, thus, carry out a longitudinal case study in a large ETO company to study and compare the characteristics and dynamics of the development process of an integrated sales and technical (ST) configurator with these of a sales configurator and a technical configurator. First, the findings uncover the nature of the integrated ST configurator development process in terms of development team formation, development planning activities, processes and activities that went wrong, and unplanned events and their handling. Second, performance evaluation with respect to several criteria contributes to a holistic picture of the development process of the integrated ST configurator. Based on the findings, we further shed light on managerial implications including the business process changes associated with the application of the integrated ST configurator and the need of having a clear, comprehensive project plan before development. To conclude, our study is expected to broaden ETO companies’ understanding of the development processes of integrated configurators and to guide them to make wise decisions in developing configurators.
Mass spectrometry- and nuclear magnetic resonance-based metabolomic studies comparing diseased versus healthy individuals have shown that microbial metabolites are often the compounds most markedly ...altered in the disease state. Recent studies suggest that several of these metabolites that derive from microbial transformation of dietary components have significant effects on physiological processes such as gut and immune homeostasis, energy metabolism, vascular function, and neurological behavior. Here, we review several of the most intriguing diet-dependent metabolites that may impact host physiology and may therefore be appropriate targets for therapeutic interventions, such as short-chain fatty acids, trimethylamine N-oxide, tryptophan and tyrosine derivatives, and oxidized fatty acids. Such interventions will require modulating either bacterial species or the bacterial biosynthetic enzymes required to produce these metabolites, so we briefly describe the current understanding of the bacterial and enzymatic pathways involved in their biosynthesis and summarize their molecular mechanisms of action. We then discuss in more detail the impact of these metabolites on health and disease, and review current strategies to modulate levels of these metabolites to promote human health. We also suggest future studies that are needed to realize the full therapeutic potential of targeting the gut microbiota.
This study investigates a policy-making problem for a local government to implement an emission trading scheme by considering the interactive production decisions of firms in its administrative ...region. The market-based allowance trading price formed freely among the firms in the region is investigated by taking into account regional environmental bearing capacities. Under the scheme, the government sets the emission reduction target of the region and allocates tradable initial allowances to firms, and firms plan their production according to their allowances on hand. A Stackelberg game model is formulated to analyze the decisions of the government and firms aiming to maximize the social welfare of the region and maximize the profit of each firm. In view of the non-concavity and discreteness of the decision model for the government, we propose a hybrid algorithm to solve the game model efficiently. This algorithm consists of a polynomial time dynamic programming, binary search, and genetic algorithm. Results reveal that i) the Stackelberg game model greatly supports local governments' policy-making on the market-driven emission allowance trading scheme, and that ii) the social welfare is a great metric for policy-making decisions on environmental regulations. The market-driven emission trading scheme is an effective mechanism for local governments to induce emission reduction through green technology adoption by firms. However, governments should set their emission reduction targets appropriately because a tight or easy regulation policy significantly affects the environmental and economic benefits as well as the social welfare.
Being able to provide companies with a number of advantages in delivering customised products, product configuration has received increasing attention from the academia and lasting interests from ...industries in the past several decades. While several surveys and reviews have been reported shedding light on specific issues in product configuration, a general overview is missing. By systematically presenting important concepts, definitions and issues underlying product configuration, such a review is of paramount importance to develop practical solutions, which ultimately contributes to efficient design, development and implementation of product configurators in practice. This study, thus, tries to fill this gap by reviewing the state-of-the-art research on product configuration. It touches on the major issues, definitions and concepts in product configuration along with the corresponding studies, such as configuration ontology, system design and development, and configuration solving. Based on the review, future research is highlighted as well.
Product configurators are recognised as critical toolkits enabling customers to co-create products with companies. Most available product configurators require customers to select suitable product ...attributes from predefined options. However, customers usually find the selection processes frustrating due to their lack of product knowledge. In view of the fact that customers often express their needs in imprecise and vague natural language, we define a new needs-based configuration mechanism and propose an implementation approach based on text embeddings and multilayer perceptron. Specifically, we leverage the massive amount of product reviews by encoding them into text embeddings. A multilayer perceptron is trained to map text embeddings to product attribute options. Experiment results indicate that the mapping has good generalisation capability to map customer needs into product configurations. The performance of our approach is comparable to that of deep learning-based approaches but with much higher efficiency in terms of computational complexity. Our needs-based configuration thus provides a quick and effective means of facilitating product customisation. It also demonstrates an innovative way of utilising customer resources in unstructured text to co-create products with companies.
In practice, manufacturers and their independent retailers in dyadic supply chains jointly make decisions by capitalizing on decision interactions while respecting the carbon emission tax and subsidy ...determined by local governments. Though studies have been published to address the joint decision-making, they involve only a very few of the important supply chain decisions due to the problem complexities. In this study, we, therefore, investigate a comprehensive joint decision-making of a manufacturer and his independent retailer considering both carbon emission tax and subsidy offered by the local government. The decisions in our study include i) the manufacturer’s technology selection, production quantities, and wholesale price and ii) the retailer’s retail price. Per the decision interactions, we analyze the decision-making problem as a Stackelberg game. The game model developed, by nature, is a bilevel 0-1 mixed nonlinear programming, and cannot be solved analytically. Considering its complexities, we further develop a nested genetic algorithm (NGA) to solve the model. Numerical examples demonstrate the applicability of the Stackelberg game model in facilitating supply chain members to jointly make decisions and the robustness of the NGA. With Sensitivity analysis, we shed light on several important managerial implications, such as, manufacturers need to identify “optimal” ranges of emissions released from producing a unit of green (or dirty) product to obtain higher profits; manufacturers need to control well their production processes so that emissions released from producing a unit of product from a green (or dirty) technology fall in “optimal” ranges contributing to higher profits.
Polysomnography (PSG) scoring is labor intensive and suffers from variability in inter- and intra-rater reliability. Automated PSG scoring has the potential to reduce the human labor costs and the ...variability inherent to this task. Deep learning is a form of machine learning that uses neural networks to recognize data patterns by inspecting many examples rather than by following explicit programming.
A sleep staging classifier trained using deep learning methods scored PSG data from the Sleep Heart Health Study (SHHS). The training set was composed of 42 560 hours of PSG data from 5213 patients. To capture higher-order data, spectrograms were generated from electroencephalography, electrooculography, and electromyography data and then passed to the neural network. A holdout set of 580 PSGs not included in the training set was used to assess model accuracy and discrimination via weighted F1-score, per-stage accuracy, and Cohen's kappa (K).
The optimal neural network model was composed of spectrograms in the input layer feeding into convolutional neural network layers and a long short-term memory layer to achieve a weighted F1-score of 0.87 and K = 0.82.
The deep learning sleep stage classifier demonstrates excellent accuracy and agreement with expert sleep stage scoring, outperforming human agreement on sleep staging. It achieves comparable or better F1-scores, accuracy, and Cohen's kappa compared to literature for automated sleep stage scoring of PSG epochs. Accurate automated scoring of other PSG events may eventually allow for fully automated PSG scoring.
With intense global competition, many manufacturing companies pursue a platform strategy to develop diverse products belonging to a family, while utilizing available manufacturing resources. In the ...past, enormous efforts have been made in investigating product platforms, which exploit platforming potential at the design stage. Researchers have recently discussed new platform concepts, which capitalize on platforming potential at different product family development stages, in addition to investigating more issues pertaining to product platforms. These efforts contribute to the continuous progress on platforming research. This study provides a review of progress on platforming. It identifies and reviews the available platform concepts, including flexible platforms, function–technology platforms, process platforms, and process parameter platforms. It also highlights several trends in platforming research, thus providing an overall picture of platform based-product family development requirements and the corresponding solutions. Based on the review, a framework is presented for future research.
Unlike most of the available configuration solutions, the integrated sales, product and production configuration is proposed to help companies realize product customization from a holistic view. It ...achieves this by determining the functional features (i.e., sales configuration), possible product alternatives (i.e., product configuration), and production process alternatives (i.e., production configuration). With the presence of multiple alternatives, it is necessary to determine final products and production processes based on the evaluation. This study, thus, evaluates the product alternatives and production process alternatives, which are configured in the integrated configuration. In line with the fact that in practice, cost and time are two of the most important elements in quotation preparation, we develop evaluation models to minimize the production costs and completion time. In addition, to provide companies with better decision-making support in selecting product offerings, the proposed configuration evaluation computes the differences in terms of cost and time among all the product and production process alternatives. With the differences in cost and time, companies can opt for suitable selection with respect to time or cost and/or other factors, e.g., strategic objectives. A case application of temperature controllers is utilized to demonstrate the results of the proposed evaluation of the integrated configuration.
•It presents a Stackelberg game model for making sustainable supply chain decisions.•It develops a nested genetic algorithm to solve the game model.•It demonstrates the applicability of the model.•It ...demonstrates the robustness of the algorithm.•It obtains several important managerial implications.
In practice, it is of paramount importance that firms make joint decisions in production planning, pricing and retailer selection while considering emission regulation. This is because the joint decisions can ensure firms to obtain higher profits while contributing to sustainable environments. However, due to the problem complexity, no models facilitating such decision making are available. This study aims to develop a model to help firms make optimal joint decisions. To model the situations where a manufacturer is the leader and the retailers are followers, we adopt the Stackelberg game theory and develop a 0–1 mixed nonlinear bilevel program to maximize the profits of both the manufacturer and his retailers. We further develop a nested genetic algorithm to solve the game model. Numerical examples demonstrate (i) the applicability of the game model and the algorithm and (ii) the robustness of the algorithm. Managerial insights are obtained, suggesting that (i) manufacturers need to identify the capacity ranges (called capacity traps) where capacity increases result in reduced profits when making decisions to optimize profits; (ii) retailers should make suitable, e.g., pricing decisions so that the manufacturers can include them in the supply chains; (iii) both manufacturers and retailers may not need to consider the carbon emission buying (or selling) price when making decisions.
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