An empirical survey: Can green marketing really entice customers to pay more?

This research integrated the Social Cognition Theory and the Engel Kollat Blackwell customers’ purchasing model (EKB model) to synthetically discuss the three kinds of possible relations comprising “does negatively entice”, “does possibly entice” and “does positively entice” between green-marketing and customers’ purchasing and payment, with consideration given to environmental-protection issues. Based on the measured results, the most contributed contention of this research not only utilized three cross-analytical theories consisting of the social cognition theory (SCT) , the Fuzzy theory (FT) and the EKB model, and the novel F-ANP of the MCDM methodology to evaluate the collected data but it also manifested that Green-marketing does possibly entice customers to pay more (GMPECPM). These measured results have distinctly stunned the fundamental assumption in the traditional green-marketing research field that customers were supposed to be willing to pay more for green products and services because they were supporting green initiatives and helping environmental-protection. Further, major future research directions were also briefly demonstrated in this research as (1) the collection data have to be strengthened to gather more empirical customer feedback, corporate management comments, and professional scholars’ reports; (2) enterprises have to resoundingly establish a green-branding initiative after successfully executing green-marketing strategies.Green Marketing (G-marketing); Multiple Criteria Decision Making (MCDM); Analytical Network Process (F-ANP).

TEXTUAL DATA MINING FOR NEXT GENERATION INTELLIGENT DECISION MAKING IN INDUSTRIAL ENVIRONMENT: A SURVEY

This paper proposes textual data mining as a next generation intelligent decision making technology for sustainable knowledge management solutions in any industrial environment. A detailed survey of applications of Data Mining techniques for exploiting information from different data formats and transforming this information into knowledge is presented in the literature survey. The focus of the survey is to show the power of different data mining techniques for exploiting information from data. The literature surveyed in this paper shows that intelligent decision making is of great importance in many contexts within manufacturing, construction and business generally. Business intelligence tools, which can be interpreted as decision support tools, are of increasing importance to companies for their success within competitive global markets. However, these tools are dependent on the relevancy, accuracy and overall quality of the knowledge on which they are based and which they use. Thus the research work presented in the paper uncover the importance and power of different data mining techniques supported by text mining methods used to exploit information from semi-structured or un-structured data formats. A great source of information is available in these formats and when exploited by combined efforts of data and text mining tools help the decision maker to take effective decision for the enhancement of business of industry and discovery of useful knowledge is made for next generation of intelligent decision making. Thus the survey shows the power of textual data mining as the next generation technology for intelligent decision making in the industrial environment

Production planning mechanisms in demand-driven wood remanufacturing industry

L'objectif principal de cette thèse est d'étudier le problème de planification de la production dans le contexte d'une demande incertaine, d’un niveau de service variable et d’approvisionnements incontrôlables dans une usine de seconde transformation du bois. Les activités de planification et de contrôle de production sont des tâches intrinsèquement complexes et difficiles pour les entreprises de seconde transformation du bois. La complexité vient de certaines caractéristiques intrinsèques de cette industrie, comme la co-production, les procédés alternatifs divergents, les systèmes de production sur commande (make-to-order), des temps de setup variables et une offre incontrôlable. La première partie de cette thèse propose une plate-forme d'optimisation/simulation permettant de prendre des décisions concernant le choix d'une politique de planification de la production, pour traiter rapidement les demandes incertaines, tout en tenant compte des caractéristiques complexes de l'industrie de la seconde transformation du bois. À cet effet, une stratégie de re-planification périodique basée sur un horizon roulant est utilisée et validée par un modèle de simulation utilisant des données réelles provenant d'un partenaire industriel. Dans la deuxième partie de cette thèse, une méthode de gestion des stocks de sécurité dynamique est proposée afin de mieux gérer le niveau de service, qui est contraint par une capacité de production limitée et à la complexité de la gestion des temps de mise en course. Nous avons ainsi développé une approche de re-planification périodique à deux phases, dans laquelle des capacités non-utilisées (dans la première phase) sont attribuées (dans la seconde phase) afin de produire certains produits jugés importants, augmentant ainsi la capacité du système à atteindre le niveau de stock de sécurité. Enfin, dans la troisième partie de la thèse, nous étudions l’impact d’un approvisionnement incontrôlable sur la planification de la production. Différents scénarios d'approvisionnement servent à identifier les seuils critiques dans les variations de l’offre. Le cadre proposé permet aux gestionnaires de comprendre l'impact de politiques d'approvisionnement proposées pour faire face aux incertitudes. Les résultats obtenus à travers les études de cas considérés montrent que les nouvelles approches proposées dans cette thèse constituent des outils pratiques et efficaces pour la planification de production du bois.The main objective of this thesis is to investigate the production planning problem in the context of uncertain demand, variable service level, and uncontrollable supply in a wood remanufacturing mill. Production planning and control activities are complex and represent difficult tasks for wood remanufacturers. The complexity comes from inherent characteristics of the industry such as divergent co-production, alternative processes, make-to-order, short customer lead times, variable setup time, and uncontrollable supply. The first part of this thesis proposes an optimization/simulation platform to make decisions about the selection of a production planning policy to deal swiftly with uncertain demands, under the complex characteristics of the wood remanufacturing industry. For this purpose, a periodic re-planning strategy based on a rolling horizon was used and validated through a simulation model using real data from an industrial partner. The computational results highlighted the significance of using the re-planning model as a practical tool for production planning under unstable demands. In the second part, a dynamic safety stock method was proposed to better manage service level, which was threatened by issues related to limited production capacity and the complexity of setup time. We developed a two-phase periodic re-planning approach whereby idle capacities were allocated to produce more important products thus increasing the realization of safety stock level. Numerical results indicated that the solution of the two-phase method was superior to the initial method in terms of backorder level as well as inventory level. Finally, we studied the impact of uncontrollable supply on demand-driven wood remanufacturing production planning through an optimization and simulation framework. Different supply scenarios were used to identify the safety threshold of supply changes. The proposed framework provided managers with a novel advanced planning approach that allowed understanding the impact of supply policies to deal with uncertainties. In general, the wood products industry offers a rich environment for dealing with uncertainties for which the literature fails to provide efficient solutions. Regarding the results that were obtained through the case studies, we believe that approaches proposed in this thesis can be considered as novel and practical tools for wood remanufacturing production planning

A Fuzzy Inference System Approach for Evaluating the Feasibility of Product Remanufacture

In the recent past, efforts have been made in enhancing sustainable manufacturing aimed at protecting the environment and saving natural resources. Among the efforts that have been explored include strategies to ensure responsible end-of-life product management so as reduce the impact on the environment and achieve effective use of resources. Towards this end, reduce, reuse and recycle product disposal strategies have found a lot of consideration in manufacturing. Of the product reuse strategies, remanufacturing has been widely applied owing to its unique feature of rendering the remanufactured product as good as new. For remanufacturers, this strategy leads to provision of quality products comparable to new their new counterparts at a reduced cost. Remanufacturing also leads to a sustainable environment through energy and material savings, as well as minimized solid wastes. Remanufacturing however, poses challenges related to collection of the returns or cores, manufacturing process planning, resource allocation, warranty estimation and redistribution. These challenges are due to product and process complexities, customer requirements, and uncertainties associated with product take back and the remanufactured products’ market-base. Key among these challenges is the remanufacturing process which is complicated, labor intensive with varying process times. In most cases the routing of these processes is stochastic in nature, based on the condition of the returned product. There is also the negative perception among consumers that remanufactured products are less superior to new ones, which calls for the need to allocate preferably longer warranty periods for the remanufactured product to induce confidence in the consumer while at the same time keeping the warranty costs low. The objectives of this study were informed by challenges faced by a local remanufacturing firm. They include: (1) a detailed study of the current remanufacturing process of the firm’s products; (2) identification of bottlenecks in the process to make recommendations for improvement; (3) develop a decision support system for assessing product remanufacture; (4) assess warranty allocation options for remanufactured product reuse. The study revealed that there are bottlenecks in the current remanufacturing process and suggested an improvement to enhance efficiency. This bottlenecks include overutilization of some of the process centers such as the diagnostic testing and the after-repair testing centers which lead to the product spending more time in the system than necessary. To improve the system performance the capacities of the bottleneck centers were increased which yielded significant reduction in the time the product spends in the system. The key contribution of this dissertation is the development of a decision support system based on a bi-level fuzzy linguistic computing approach. This model integrates qualitative and quantitative product attributes in determining the remanufacturability of a product. The fuzzy-based model established remanufacturability metric, herein referred to as an index, is applied to assess the feasibility of remanufacturing two products that were used as a case study. A number of warranty scenarios are considered to ascertain the impact of different warranty periods on the cost of warranty. The results show that the additional warranty cost for product reuse is a function of the period of first use and the residual life of the produc

Lean, agile, resilient and green supply chain management interoperability assessment methodology

Dissertação para obtenção de grau de Mestre em Engenharia e Gestão Industrial (MEGI)Supply Chain Management has become a tactic asset for the current global competition situation. Innovative strategies such as Lean, Agile, Resilient and Green emerged as a response, requiring high levels of cooperation and of great complexity. However, the strategic alignment of operations with partners in supply chains is affected by lack of interoperability. The present work provides a framework to enhance SC competitiveness and performance by assessing interoperable SCM Practices applied in automotive industry. Through a pragmatic interoperability approach, this methodology describes in detail the form of application using analytical hierarchical process (AHP) and Fuzzy sets as support decision making models, ensuring a systematic approach to the analysis of interoperability with appropriate criteria for assessment of situations that require high levels of collaboration between partners. Through a case study in a Portuguese automaker, it was possible to test the methodology and analyse which areas lack interoperability in the implementation of SCM practices

The Creation Of Tools And Models To Characterize And Quantify User-centered Design Considerations In Product And System Developm

Ease of use differentiates products in a highly competitive market place. It also brings an added value that culminates in a higher degree of customer satisfaction, repeated business, increased sales, and higher revenue. User-centered design is a strategic asset that companies can use to improve their customer relationships by learning more about their customers, and increase their sales. In today\u27s economy, the measurement of intangible assets such as user experience has become a major need for industries because of the relationship between user-centered design and organizational benefits such as customer loyalty. As companies realize that the inclusion of user-centered design concepts in product or system design are a key component of attracting and maintaining customers, as well as increasing revenue, the need for quantitative methods to describe these benefits has become more urgent. The goal of this research is to develop a methodology to characterize user-centered design features, customer benefits and organizational benefits resulting from developing products using user-centered design principles through the use of an integrated framework of critical factors. Therefore, this research focuses on the identification of the most significant variables required to assess and measure the degree of user-centered design (UCD) characteristics included in the various aspects of product development such as physical design features, cognitive design attributes, industrial design aspects and user experience design considerations. Also this research focuses on the development of assessment tools for developers to use when evaluating the incorporation of user-centered design features in the creation of products and systems. In addition, a mathematical model to quantify the inclusion of UCD factors considered in the design of a product and systems is presented in this research. The results obtained using the assessment tools and the mathematical model can be employed to assess the customer benefits and organizational benefits resulting from including user-centered design features in the creation of products and systems. Overall, organizational benefits such as customer loyalty, company image, and profitability are expected to be impacted by the company\u27s capability to meet or exceed stated design claims and performance consistency while maintaining aesthetic appeal, long product life, and product usefulness. The successful completion of this research has produced many beneficial research findings. For example, it has helped characterize and develop descriptors for estimating critical quantitative and qualitative components, sub-components, and factors influencing user-centered design that are related to customer and organizational benefits through the use of fuzzy set modeling. In addition, the development of specific tools, methods, and techniques for evaluating and quantifying UCD components resulted from this study

New Family of Stream Ciphers as Physically Clone-Resistant VLSI-Structures

A new large class of $2^{100}$ possible stream ciphers as keystream generators KSGs, is presented. The sample cipher-structure-concept is based on randomly selecting a set of 16 maximum-period Nonlinear Feedback Shift Registers (NLFSRs). A non-linear combining function is merging the 16 selected sequences. All resulting stream ciphers with a total state-size of 223 bits are designed to result with the same security level and have a linear complexity exceeding $2^{81}$ and a period exceeding $2^{161}$. A Secret Unknown Cipher (SUC) is created randomly by selecting one cipher from that class of $2^{100}$ ciphers. SUC concept was presented recently as a physical security anchor to overcome the drawbacks of the traditional analog Physically Unclonable Functions (PUFs). Such unknown ciphers may be permanently self-created within System-on-Chip SoC non-volatile FPGA devices to serve as a digital clone-resistant structure. Moreover, a lightweight identification protocol is presented in open networks for physically identifying such SUC structures in FPGA-devices. The proposed new family may serve for lightweight realization of clone-resistant identities in future self-reconfiguring SoC non-volatile FPGAs. Such self-reconfiguring FPGAs are expected to be emerging in the near future smart VLSI systems. The security analysis and hardware complexities of the resulting clone-resistant structures are evaluated and shown to exhibit scalable security levels even for post-quantum cryptography.Comment: 24 pages, 7 Figures, 3 Table