Using Microservices to Customize Multi-Tenant SaaS: From Intrusive to Non-Intrusive

Customization is a widely adopted practice on enterprise software applications such as Enterprise resource planning (ERP) or Customer relation management (CRM). Software vendors deploy their enterprise software product on the premises of a customer, which is then often customized for different specific needs of the customer. When enterprise applications are moving to the cloud as mutli-tenant Software-as-a-Service (SaaS), the traditional way of on-premises customization faces new challenges because a customer no longer has an exclusive control to the application. To empower businesses with specific requirements on top of the shared standard SaaS, vendors need a novel approach to support the customization on the multi-tenant SaaS. In this paper, we summarize our two approaches for customizing multi-tenant SaaS using microservices: intrusive and non-intrusive. The paper clarifies the key concepts related to the problem of multi-tenant customization, and describes a design with a reference architecture and high-level principles. We also discuss the key technical challenges and the feasible solutions to implement this architecture. Our microservice-based customization solution is promising to meet the general customization requirements, and achieves a balance between isolation, assimilation and economy of scale

Why Customers Value Mass-customized Products: The Importance of Process Effort and Enjoyment

We test our hypotheses on 186 participants designing their own scarves with an MC toolkit. After completing the process, they submitted binding bids for "their" products in Vickrey auctions. We therefore observe real buying behavior, not merely stated intentions. We find that the subjective value of a self-designed product (i.e., one's bid in the course of the auction) is indeed not only impacted by the preference fit the customer expects it to deliver, but also by (1) the process enjoyment the customer reports, (2) the interaction of preference fit and process enjoyment, and (3) the interaction of preference fit and perceived process effort. In addition to its main effect, we interpret preference fit as a moderator of the valuegenerating effect of process evaluation: In cases where the outcome of the process is perceived as positive (high preference fit), the customer also interprets process effort as a positive accomplishment, and this positive affect adds (further) value to the product. It appears that the perception of the self-design process as a good or bad experience is partly constructed on the basis of the outcome of the process. In the opposite case (low preference fit), effort creates a negative affect which further reduces the subjective value of the product. Likewise, process enjoyment is amplified by preference fit, although enjoyment also has a significant main effect, which means that regardless of the outcome, customers attribute higher value to a self-designed product if they enjoy the process. The importance of the self-design process found in this study bears clear relevance for companies which offer or plan to offer MC systems. It is not sufficient to design MC toolkits in such a way that they allow customers to design products according to their preferences. The affect caused by this process is also highly important. Toolkits should therefore stimulate positive affective reactions and at the same time keep negative affect to a minimum. (authors' abstract

Extending the product portfolio with ‘devolved manufacturing’: Methodology and case studies

Current research by the developers of rapid prototyping systems is generally focused on improvements in cost, speed and materials to create truly economic and practical economic rapid manufacturing machines. In addition to being potentially smarter/faster/cheaper replacements for existing manufacturing technologies, the next generation of these machines will provide opportunities not only for the design and fabrication of products without traditional constraints, but also for organizing manufacturing activities in new, innovative and previously undreamt of ways. This paper outlines a novel devolved manufacturing (DM) ‘factory-less’ approach to e-manufacturing, which integrates Mass Customization (MC) concepts, Rapid Manufacturing (RM) technologies and the communication opportunities of the Internet/WWW, describes two case studies of different DM implementations and discusses the limitations and appropriateness of each, and finally, draws some conclusions about the technical, manufacturing and business challenges involved

Decision support for build-to-order supply chain management through multiobjective optimization

This paper aims to identify the gaps in decision-making support based on multiobjective optimization for build-to-order supply chain management (BTOSCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting multiobjective optimization (MOO) techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted and future research directions to better exploit the decision support capabilities of MOO are proposed

Decision support for build-to-order supply chain management through multiobjective optimization

This is the post-print version of the final paper published in International Journal of Production Economics. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2010 Elsevier B.V.This paper aims to identify the gaps in decision-making support based on multiobjective optimization (MOO) for build-to-order supply chain management (BTO-SCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting MOO techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted. Future research directions to better exploit the decision support capabilities of MOO are proposed. These include: reformulation of the extant optimization models with a MOO perspective, development of decision supports for interfaces not involving manufacturers, development of scenarios around service-based objectives, development of efficient solution tools, considering the interests of each supply chain party as a separate objective to account for fair treatment of their requirements, and applying the existing methodologies on real-life data sets.Brunel Research Initiative and Enterprise Fund (BRIEF