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Mass customization has yet to fulfill its original purpose as established by marketing researchers to become an alternative to mass production, largely due to its inability to achieve mass market levels of efficiency. The purpose of this study is to survey consumer's perceptions, willingness and capabilities of participating in a mass customization system, and understand the implications of its findings related to an alternative production system, generative customization.

After an extensive literature review of mass customization, consumer behavior, complex adaptive systems and generative design, a survey was conducted across US and Swedish consumers relative to their willingness and perceptions regarding mass customization, with hypotheses based upon extant research standards.

The survey results found that consumers are ambivalent toward mass customization in mass markets, and a conceptual alternative (generative customization) appears to achieve, at least conceptually, the necessary objectives relative to product design conceptualization and fulfillment that mass customization cannot achieve.

A lack of significant findings from extant research regarding consumer perceptions and tolerances regarding mass customization in mass markets is a limitation to this study. The discussion of a new concept (generative customization) as a viable alternative to mass customization as a result of the survey findings needs to be validated empirically in future research.

The paper empirically validates a definition of mass customization as a complementary rather than an alternative to mass production. It also introduces and develops the concept of generative customization as viable alternative to mass production, albeit one that must be empirically validated in future research.

The purpose of this paper is to address the problem in research of a lack of a holistic conceptual framework related to incremental and discontinuous innovation. Too often, the term “innovation” is used without an understanding of how it can be applied in a product design and supply chain fulfillment system. In this study, the goal is to develop a holistic “innovation continuum” to treat innovation as a complex adaptive system (CAS).

A comprehensive literature review was conducted, and from it, four propositions and a conceptual framework were developed.

The authors determined that an “innovation continuum” can be established through the use of a complex adaptive system. Two, incremental innovation is determined to possess adaptive qualities, and can be enhanced through the use of collaboration and evolutionary algorithms. Three, discontinuous innovation is established as a creative process enabled through expert designers, and improved through the use of generative design. Next, a supply chain system for incremental innovation can be assisted by the use of adaptive systems, but it is not proven that a generative customization system (for discontinuous innovation) can be improved through the use of a CAS.

The paper has established an “innovation continuum” linking incremental and discontinuous innovation within one holistic system. It establishes the use of evolutionary algorithms to improve the viability of incremental innovation, and generative design for discontinuous innovation. Finally, the concept of generative customization as an end to end product design and supply chain fulfillment solution for discontinuous innovation is established.

This study aims to create and deploy new configurations of resources via understanding issues concerning generative knowledge integration (KI) to create a customer‐centric relationship management system.

A qualitative case study of a public‐listed housing developer was conducted to analyze its main issues and conceptualize the underlying generative knowledge integration process.

Issues concerning generating KI were identified from the case study. The conceptualization of generative KI encompasses three main generative KI mechanisms, knowledge conceptualization, knowledge convergence, and knowledge assimilation, that are connected by three generative KI processes: accessing and exchanging knowledge, articulating and exchanging knowledge, and combining and exchanging knowledge.

The importance of understanding the concept of generative knowledge integration for practitioners is emphasized, and suggestions are given to promote the deployment of knowledge integration generation throughout system development.

The research conducted is unique in that a new model of generative knowledge integration is proposed, contributing to the knowledge integration literature in terms of the uncovering the three new generative KI mechanisms and processes.

This paper aims to present a pilot study’s aims to identify opportunities and limits deriving from the use of low-cost 3D printing (3DP), fused deposition modelling (FDM), open-source technologies in co-design and co-production processes involving persons with rheumatic diseases (RDs).

In the paper, the authors outline why the use of low-cost, entry-level FDM can be meaningful for this scenario, implying a complete sharing of the design and the production phases of small assistive devices. The +TUO process is composed of several stages, among which the generative session represents the core.

This study highlights as the introduction of this low-cost technology in co-generative processes with people with RDs is a real challenge that can lead to new products and solutions, and that can sustain a social and local manufacturing approach for people facing a specific disablement.

This research is a first step of a broader research, new researches are going to explore further details related with the technology and of the adopted method.

Involving actively, the end user during the creation process can bring advantages such as meeting more precisely their needs and create innovative products, as shown in the text.

For people living with RDs, an occupation is important to sustain a process of empowerment. Adopting assistive devices supports daily activities and facilitates the occupation.

+TUO is a pilot study that explore a topic already discussed in the scientific arena, without focusing on the specific use of low-cost 3DP technologies.

This viewpoint article explores the transformative capabilities of large language models (LLMs) like the Chat Generative Pre-training Transformer (ChatGPT) within the property valuation industry. It particularly accentuates the pivotal role of prompt engineering in facilitating valuation reporting and advocates for adopting the “Red Book” compliance Chain-of-thought (COT) prompt engineering as a gold standard for generating AI-facilitated valuation reports.

The article offers a high-level examination of the application of LLMs in real estate research, highlighting the essential role of prompt engineering for future advancements in generative AI. It explores the collaborative dynamic between valuers and AI advancements, emphasising the importance of precise instructions and contextual cues in directing LLMs to generate accurate and reproducible valuation outcomes.

Integrating LLMs into property valuation processes paves the way for efficiency improvements and task automation, such as generating reports and drafting contracts. AI-facilitated reports offer unprecedented transparency and elevate client experiences. The fusion of valuer expertise with prompt engineering ensures the reliability and interpretability of valuation reports.

Delineating the types and versions of LLMs used in AI-generated valuation reports encourage the adoption of transparency best practices within the industry. Valuers, as expert prompt engineers, can harness the potential of AI to enhance efficiency, accuracy and transparency in the valuation process, delivering significant benefits to a broad array of stakeholders.

The article elucidates the substantial impact of prompt engineering in leveraging LLMs within the property industry. It underscores the importance of valuers training their unique GPT models, enabling customisation and reproducibility of valuation outputs. The symbiotic relationship between valuers and LLMs is identified as a key driver shaping the future of property valuations.

The purpose of this paper is to identify and classify the available types of 3D printing services, with the scope of determining the potential implications that such services could have on the supply chains of manufacturing firms and creating a research agenda for future studies.

The authors review the current literature on the potential supply chain impacts of 3D printing and evaluate the 3D printing services provided by 404 firms in selected European markets.

The results show that 3D printing services form a rapidly evolving industry, with new service providers entering the market on a regular basis. Evidence from the European markets investigated suggests that services can be classified into three distinct categories: generative, facilitative and selective services.

This paper represents an attempt to take stock of a fast-moving and potentially paradigm-shifting market. The implications are dynamic as new applications, business models and techniques are continually being developed. Further studies are required to substantiate the findings.

Three categories of 3D printing services that could significantly impact supply chain configurations of the future are proposed. Several issues specific to 3D printing services raised in the research agenda require further scrutiny and substantiation before services can reach their full potential.

This paper provides an overview of the growing 3D printing services industry, highlighting how the market might change as additive manufacturing technology matures.

The purpose of this paper is to provide an analysis of how virtual-social-physical (VSP) convergence can affect different types of project manufacturing. In particular, VSP convergence that involves combining the read-write functionality of Web 2.0 and related social media together with digital tools for virtual design and for physical manufacturing.

Literature review and interviews with experts in technologies covering VSP convergence: digital data capture, photogrammetry, generative computation, Web 2.0 and social media, digitally driven manufacturing.

VSP convergence can enable the replacement of slow and expensive traditional project manufacturing practices with much faster and less expensive digitally driven technologies.

There are new opportunities for expansion of some types of project manufacturing. Notably, there are opportunities in non-industrial developing countries because VSP convergence reduces reliance on industrial infrastructure for the manufacturing of goods. By contrast, opportunities may be limited for expansion of established project manufacturing companies with exclusive brands.

The originality is that VSP convergence is related to different types of project manufacturing. Based on VSP convergence, traditional types and new types of project manufacturing are categorized together for the first time. The value of this paper is that it is explained how VSP convergence can address barriers to expansion of different types of project manufacturing.

Despite all the recent achievements in the field of interactive marketing and artificial intelligence (AI), it is important to consider the ethical implications of these technologies. This paper explains the concept of corporate digital responsibility (CDR) and how it is affected by new advances in AI.

The authors build on the work of Wirtz et al., (2023) and derive several managerial implications for the challenges that AI poses to CDR. CDR refers to a service company's ethical and fair use of data and technology within its digital service ecosystem. It involves establishing standards, protecting customer privacy, conducting external audits and striving for an equitable power dynamic between service firms and their partners.

Despite the risks involved, many companies are not prioritizing good CDR practices. Financial benefits from the collection and use of consumer data, improved customer experience through AI-driven customization and personalization, cost reduction through service automation and the trade-offs between organizational goals and CDR practices can prevent companies from prioritizing good CDR practices.

This is one of the first articles in the service domain to take the concept of CDR and apply it to recent developments in generative AI.

The emergence of powerful AI tools presents opportunities and challenges. Research opportunities include responsible business restructuring, responsible service automation to ensure fairness and human oversight, addressing dehumanization of service delivery, responsible customer profiling to address privacy and discrimination concerns and preventing AI misuse.

Generative Production Systems are generative design computation that is linked to optimal physical production. They can improve the design and production of products which have unique geometries. The purpose of this paper is to introduce a preliminary methodology for Generative Production Systems.

The paper takes the form of a literature review investigating the structures and formats of successful methodologies. The literature review also investigates Generative Production Systems' theoretical foundations, development and implementations.

The potential of Generative Production Systems is restricted because enabling information is fragmented and difficult to access. In other fields, such barriers have been overcome through the introduction of methodologies that provide guiding principles, rules and strategies (P‐R‐S). The P‐R‐S type of methodology structure is suitable for Generative Production Systems.

The use of Generative Production Systems requires more upfront investment than the use of CAD/CAM software packages. However, they require little, or no, human input after they are set‐up. The preliminary methodology provides structured guidance about how to set up a Generative Production System. Further, the explanatory text enables wider understanding of Generative Production Systems, and how they can improve design and production.

An analysis is provided for the structure and format of successful methodologies in general. A preliminary methodology for Generative Production Systems is introduced. Further, the paper provides an overview of the disadvantages and advantages of Generative Production Systems compared to typical CAD/CAM software packages.

Modular construction is widely adopted and used in the construction industry to improve construction performance with respect to both efficiency and productivity. The evaluation of design options for modular construction can be iterative, and thus automation is required to develop design alternatives. This research aims to explore the potential of utilizing the generative design approach to automate modular construction for residential building structures in urban areas such as New York City.

The proposed research methodology is investigated for a systematic approach to parametrize design parameters for modular construction layout design as well as incorporate design rules/parameters into modularizing design layouts in a Building Information Modeling (BIM) environment. Based on current building codes and necessary inputs by the user, the proposed approach enables providing recommendations in a generative design method and optimizes construction processes by performing analytical calculations.

The generative design has been found to be efficient in generating layout designs for modular construction based on parametric design. The integration of BIM and generative design can allow industry practitioners to fast generate design layout with evaluations from constructability perspectives.

This paper has proposed a new approach of incorporating generative design with BIM technologies to solve module layout generations by considering design and constructability constraints. The method can be further extended for evaluating modular construction design from manufacturability and assembly perspectives.