An Integrated Decision Support System Considering Interdependencies Between Time-to-Market and Market Diffusion under Competition

AbstractIndustry faces fundamental challenges as new competitors from emerging countries enter markets. Thus, competition increases and time-to- market as intermediate span between R&D and series production gets more important. Additionally, customers ask for more individualized products. However, the resulting increase in product variety leads to rising complexity and costs and thereby, limited resources have to be allocated to a multitude of parallel product development projects.To tackle these challenges and stay successful, companies aim at decreasing time-to-market with constant or even lower resource input. While complexity management and resource allocation have extensively been discussed for R&D and series production, approaches for the intermediate time-to-market phase are still scarce.Against this background, the aim of this contribution is to analyze the interrelations between time-to-market and resource allocation in a competitive environment with a decision support system. To reach this aim, we present a system-dynamics simulation model analyzing the market diffusion of a product in a competitive environment. with the proposed model, we are able to derive information on interdependencies between resource input and time-to-market depending on competitors’ behavior.We apply the model to the gas turbine industry. In order to do so, we create a dataset merging recent data from literature with information gathered in expert interviews. Thus, we are able to quantify the parameters of the model. Results are presented highlighting the interdependencies between resources and time-to-market for the competitive environment of the gas turbine market

Exploring the Sources of Design Innovations: Insights from the Computer, Communications and Audio Equipment Industries

Whereas business research has focused on the impact of design innovations on market response and financial performance, the sources of design innovations, as opposed to those of technological innovations, have largely escaped investigation. In this research, we examine the organizational, financial, and environmental drivers of design innovations and how they contrast to technological innovations. Our study utilizes a unique dataset encompassing a 10-year window of innovation output drawn from the computer, communications, and audio and video equipment manufacturing industries. Our results suggest that design innovations are driven primarily by investments in research and development and slack organizational resources. Interestingly, we find that design innovations are more prevalent in smaller but fast-growing markets as opposed to technology innovations, which are prevalent in larger markets. Contrary to expectations, we find no association between marketing investments and design innovations. Our research contributes to the extant business literature by considering the sources of design innovations separately from the sources of technology innovations. We also contribute to the literature by distinguishing design and technology patents, developing a deeper understanding of design innovation, and illuminating a lesser understood source of competitive advantage for firms

Exploration and exploitation activities for design innovation

This paper focuses on design innovation: that is, the development of products that are new in terms of products’ appearance, the emotions products evoke, and/or the way they enable customers to express their identity. Although prior research acknowledges the importance of design innovation for product and organisational performance, studies on how to manage design innovation are relatively scarce. The present study attempts to fill this gap by investigating design innovation and its management in terms of the degree of exploration and exploitation activities and designers’ decision freedom when developing new offerings. We collected data on projects in which external design consultancies were actively involved during the development process (n = 83). For each project, we surveyed both the external senior designer a

Value Cocreation for Service Innovation: Examining the Relationships between Service Innovativeness, Customer Participation, and Mobile App Performance

Service innovation is critical to firms’ competitive advantage and, thus, firms desire to make their services increasingly innovative. However, the relationship between the innovativeness and performance of a new service is unclear. Conflicting findings and the related literature suggest that service innovativeness is multidimensional and its impact on performance could be nonlinear. However, limited research has studied these aspects, both theoretically and empirically. Furthermore, prior research has mainly considered customers as inputs to value creation, which may not capture their precise role. Drawing on service-dominant logic, we propose two dimensions of service innovativeness, namely novelty and intensity, which differentially influence the performance of a new service. We further posit that customers are part of the value cocreation process, thereby directly and indirectly affecting new service performance. The model was tested using a panel dataset of 234 mobile apps over 14 months. Results indicate important asymmetries in the impacts of novelty and intensity on mobile app performance: novelty shows a curvilinear relationship with mobile app performance whereas intensity shows a positive linear relationship. Furthermore, customer participation positively impacts mobile app performance and positively moderates the effects of intensity and novelty on mobile app performance

How Innovation affects Users’ Emotional Responses: Implications for Product Success and Business Sustainability.

The market is experiencing an expanding range of products, prompting manufacturing companies to differentiate themselves from competitors by moving away from conventional concepts. However, these innovations often fail to meet consumer expectations, leading to product failure, and consequently, an unsustainable evolution of the market and the business. This unsustainability requires designers to adapt innovations to align with consumer needs and desires. Understanding and validating these adaptations can be achieved by examining users’ emotional responses to innovative products. The objective of this study is to assess the influence of innovation in the development of new successful products, sales performance, and, therefore, business sustainability. This evaluation is based on the perceptions of potential consumers through the analysis of users’ emotional responses to various new product concepts at different design stages. A case study presents the evaluation of 48 new interactive lamp concepts categorized into relaxation, study, and leisure topics. The target audience for these concepts is consumers aged 18 to 24. The designs were developed by 12 teams of final-year industrial design students using insights from a prior psychographic study involving over 800 potential consumers. The findings highlight differences in users’ perceptions of innovative and traditional products across topics. These differences relate to users’ interest, intuitiveness, and desirability toward a product. Generally, traditional product concepts are perceived as more intuitive, but users show greater interest and desire for innovative concepts, with some variations among the analyzed topics. The business environment is encouraged to share these data with new product-development teams to achieve sustainable market and business growth.Partial funding for open access charge: Universidad de Málag

Design and Evaluation of Product Aesthetics: A Human-Machine Hybrid Approach

Aesthetics are critically important to market acceptance in many product categories. In the automotive industry in particular, an improved aesthetic design can boost sales by 30% or more. Firms invest heavily in designing and testing new product aesthetics. A single automotive "theme clinic" costs between \$100,000 and \$1,000,000, and hundreds are conducted annually. We use machine learning to augment human judgment when designing and testing new product aesthetics. The model combines a probabilistic variational autoencoder (VAE) and adversarial components from generative adversarial networks (GAN), along with modeling assumptions that address managerial requirements for firm adoption. We train our model with data from an automotive partner-7,000 images evaluated by targeted consumers and 180,000 high-quality unrated images. Our model predicts well the appeal of new aesthetic designs-38% improvement relative to a baseline and substantial improvement over both conventional machine learning models and pretrained deep learning models. New automotive designs are generated in a controllable manner for the design team to consider, which we also empirically verify are appealing to consumers. These results, combining human and machine inputs for practical managerial usage, suggest that machine learning offers significant opportunity to augment aesthetic design

The Influence of Mating Motives on Reliance on Form Versus Function in Product Choice

Through five experiments, this research examined and supported the central hypothesis that a casual mating motive promotes higher reliance on form in product evaluation and choice, whereas a committed mating motive promotes higher reliance on function. Particularly, compared to a committed mating motive, a casual mating motive was associated with the relative preference for product options superior in form attributes as opposed to options superior in function attributes (Study 1, Study 2, and Study 4). This research applied three different operationalizations of mating motives. In studies 1 and 5, contextual priming was used. Studies 2 and 3 employed chronic mating motives using sociosexuality. Study 4 utilized a physiological operationalization by assessing fertility in women’s menstrual cycle. It was demonstrated that the underlying mechanism for this effect lied in differential reliance on form- versus function-related product cues (Study 2). In addition, two moderating effects were demonstrated. First, Study 3 provided support for the moderating role of information ambiguity type (form vs. function). Second, Study 5 showed the interactive effect of mating motive and product choice strategy. By directing consumers to pursue a form-based versus a function-based strategy, Study 5 illustrated the effect of congruence between mating motives and choice strategy on product valuation such that consumers with a casual mating motive were willing to spend more on their product choices when they were based on form than when they were based on function, whereas consumers with a committed mating motive indicated higher willingness to pay when the product choices were made based on function than when they were made based on form. Finally, theoretical contributions and managerial implications were discussed

Deep visual generation for automotive design upgrading and market optimising

The rising levels of homogeneity of modern cars in terms of price and functions has made exterior styling increasingly vital for market success. Recently, researchers have attempted to apply deep learning, especially deep generative models, to automotive exterior design, which has enabled machines to deliver diverse novel designs from large-scale data. In this thesis, we argue that recent advancements in deep learning techniques, particularly in deep generation, can be utilised to facilitate different aspects of automotive exterior design, including design generation, evaluation, and market profit predicting. We conducted three independent studies, each providing tailored solutions to specific automotive design scenarios. These include: a study focused on adapting the latest deep generative model to achieve regional modifications in existing designs, and evaluating these adjustments in terms of design aesthetic and prospective profit changes; another study dedicated to developing a predictive model to assess the modernity of existing designs regarding the future fashion trends; and a final study aiming to incorporate the distinctive shape characteristics of a cheetah into the side view designs of cars. This thesis has four main contributions. First, the developed DVM-CAR dataset is the first large-scale automotive dataset containing designs and marketing data over 10 years. It can be used for different types of research needs from multiple disciplines. Second, given the inherent constraints in automotive design, such as the need to maintain “family face”, and the fact that unconstrained design generation can be seen as a special form of regional modification, our research distinctively focuses on the regional modifications to existing designs, a departure from existing studies. Third, our studies are the first works that integrate the design modules with market profit optimisation. This reforms the traditional product design optimisation frameworks by replacing the abridged design profiles with graphical designs. Finally, the proposed data-driven measures offer effective approaches for automotive aesthetic evaluation and market forecasting, including approaches that can make assessments from a dynamic perspective by examining the evolving fashion trends