Search results

This paper aims to explore how customer involvement unfolds in the development of a smart product. Smart product development poses new challenges to firms. In particular, the buyers’ and users’ involvement has shown novel dynamics in smart product development. These peculiarities are linked with the specific characteristics of the digital technology embedded into the smart products. This study’s rationale is to analyse the frictions arising from potential divergent objectives between the focal firm and its customers when digital technologies are embedded in traditional products.

This study adopted an explorative and qualitative approach to investigate new emerging dynamics of customer involvement during technological development. A coffee machine producer is selected as a case study to uncover new insights and a novel perspective on the phenomenon of customer involvement in smart product development. Data analysis followed an abductive approach that allowed to identify the dimensions of friction emerging during the technological development process.

The case study analysis depicts that smart product development presents novel customer involvement dynamics. In particular, this study abductively identifies dimensions of friction emerging between the focal firm and buyers/users. Friction arises in the technological interface between the actors involved. These dimensions of friction address the complexities of developing technology in terms of smart products with customer involvement. This study suggests that embedding of technology into an existing product might change how customers are involved.

Even though customer involvement in product innovation has been extensively studied in management literature, this paper focused on a new type of innovation, smart products. To the best of the authors’ knowledge, no previous studies have yet empirically explored customers’ involvement while embedding digital technologies into existing products to create smart products. In particular, this study sheds light on the dimensions of friction emerging between the focal firm and the actors of the business network. This study unfolds novel contributions to the Industrial Marketing and Purchasing literature on technological development.

This conceptual study investigates the adoption of education technology (EdTech) products among college students, focusing on identifying the key factors influencing the adoption process within educational institutions. Technology integration in education has rapidly gained prominence, with EdTech offering innovative solutions to enhance teaching and learning experiences. However, understanding the determinants that affect EdTech adoption remains critical for its successful implementation and impact. This paper aims (1) to identify the factors influencing the adoption of EdTech by college students (2) to create a conceptual model that shows the connections between the elements that lead to college students adopting EdTech.

The research employed a mixed-methods approach, combining qualitative data analysis and conceptual modeling to achieve the objectives. The underlying knowledge required to create a qualitative data gathering tool was obtained through a thorough literature analysis on innovation dissemination, educational psychology and technology adoption. College students, teachers and administrators participated in semi-structured interviews, focus groups and surveys to provide detailed perspectives on their attitudes about and experiences with EdTech. The Scopus and Web of Science databases are searched for relevant information in an organized manner in order to determine the factors influencing the adoption of EdTech. Second, an extended version of the technology adoption model is adopted to develop a qualitative data-based conceptual framework to analyze EdTech adoption in the Indian context.

Overall, by highlighting the critical components that emotionally influence college students' adoption of EdTech products in educational institutions, this course adds to the body of information already in existence. The conceptual framework model serves as a roadmap for educational stakeholders seeking to leverage EdTech effectively to enrich the learning environment and improve educational outcomes. By recognizing the significance of the identified factors, academic institutions can make informed decisions to foster a climate conducive to successful EdTech integration.

A comprehensive conceptual framework model was developed based on qualitative data analysis to illustrate the interrelationships between the identified factors influencing EdTech adoption. This model presents a valuable tool for educational institutions, policymakers and EdTech developers to comprehend the complex dynamics of implementing these technological solutions.

The findings of this study demonstrated a number of important variables that affect the uptake of EdTech products in educational settings. These factors encompassed technological infrastructure, ease of use, perceived usefulness, compatibility with existing academic practices, institutional support, financial constraints and individual attitudes towards technology. Additionally, the research explored the significance of institutional preparation for embracing technological advancements as well as the influence of socio-cultural elements.

In this paper, we examine the comparative advantage of Korea and China while focusing on their technology level. The three digit SITC (Standard International Trade Classification) data is classified by technology level and the revealed comparative advantage (RCA) is derived from 1992-2009 by using UN COMTRADE data. For careful interpretation of the comparative advantage and technology levels, we also examined intra-industry trade and unit values of bilateral Korea-China trade, and semi-conductor industry technology. We found that the revealed comparative advantage has moved from low technology products to high technology products in Korea. China still maintains a comparative advantage in low technology products such as textiles and clothing, but at the same time, China’s high and medium-high technology products have recently gained a comparative advantage. The perception that China only has a comparative advantage for labor intensive products with low technology should be changed based on our analysis. However, China’s advancement in technology should not be overestimated. When comparing the unit value of basic materials of Korea’s and China’s exports, we found that Korea’s export product prices are on average higher than that of China’s, although the gap is reducing. A wider technology gap between Korea and China still exists in the semi-conductor industry, which is one of the most advanced high technology industries throughout the world.

This study aims to verify the effectiveness and efficiency of corporate technology innovation activities.

This study empirically analyzes the effects of research and development (R&D) capability on patent and new product development achievements on innovation-type small- and medium-sized enterprises (SMEs) by using the “Report on Korean Innovation Survey 2010: Manufacturing Sector” data released by the Science and Technology Policy Institute.

The results of the study indicate that staffing of the concentration of R&D human resource team and efforts toward open innovation are essential factors for the creation of corporate performance.The number of persons of the concentration R&D team in particular makes up essential resources for patent acquisition and new product development. In addition, in case of an SME’s with relatively poor resources, it is necessary to acquire resources, both material and immaterial, learn from the external R&D activities and internalize those into key corporate capabilities rather than step up the R&D activities on their own.

The results of this study indicate that innovative small enterprises need to secure the number of R&D human resource members for maintaining sustainable competitiveness and securing market share. Therefore, a strategy is needed that would enable employing and raising excellent human resource in the quantitative and qualitative aspects. However, in the circumstances that small enterprises suffer difficulty in securing professional human resource for R&D compared to large enterprises, as there is a limitation for securing human resource for R&D from only the dimension of enterprises, governmental and political support is thought to be necessary for securing good-quality human resource for R&D. Accordingly, the results of this study provide many implications for the necessity of detailed methodology on how to expand professional human resource for R&D among supporting policies for technical innovative enterprises and to establish innovative strategies of enterprises.

The Internet of Things (IoT) real-time data collection can help to more efficiently optimize and control companies' internal processes. Prior research analyzed IoT benefits and potential applications. Nevertheless, there is little empirical evidence and theoretical understanding of how IoT impacts new product development (NPD). This article aims at narrowing this gap.

In total, 54 case studies were selected from an IoT database – IoT ONE. IoT ONE has a section on NPD. NPD was divided into three phases: discovery, development and commercialization. The adopted IoT technology maturity level was also analyzed. A content analysis was carried out to identify the impacts of IoT in NPD.

This study’s findings capture the emerging patterns of IoT adoption and its impact on NPD. Of the total, 33 IoT adoption cases in the sample were in the machinery and equipment sector. Adopted technologies were at least two years old in 85% of the sample. Only 15% adopted cutting edge technologies (less than 2 years old). Key actors (e.g. vendors) facilitate IoT adoption. By a small margin, the larger impacts of IoT were in the commercialization phase, where it was primarily applied to improve and optimize production processes, to better execute and synchronize new products launching, and to increase the factories' productive capacity. In the discovery phase, IoT was mainly used to identify new opportunities in the market and to collect customer data, to generate a better customer experience. In the development phase, IoT allows greater integration across departments, increasing internal collaboration and allowing more flexible NPD.

Many articles studied the impact of information technologies in NPD. Few address the impact of IoT in NPD. IT tells about the impact of better communications with relevant people. IoT tells about machine acquired information and knowledge. This is new, much broader and deals with quite different impacts on NPD.

The use of modern technologies of the fourth industrial revolution, commonly known as “Industry 4.0” (I4.0), is believed to have considerable potential for product customisation. In this context, this paper aims to explore whether or not using these technologies impacts customer participation (CP) in a firm's new product development (NPD) process.

To empirically test the proposed relationships, the authors collected the North Italian manufacturing firms' data and applied regression analysis.

Empirical results indicate that, on the one hand, the technologies have their specific and individual impacts, and on the other hand, the firms which use more I4.0 technologies allow more customer participation in their product design and production process. This positive impact is more robust in product design than in the production process.

Managers aiming to benefit from CP should broaden the scope of adopting I4.0 technologies and consider different roles concerning the design and production phases of the new product development process. Recognising the importance and allowing CP in NPD will enable firms to meet the customised demands.

To the best of the authors' knowledge, the proposed relationships of this study have been extensively debated theoretically in the I4.0 context but never empirically tested before. It is one of the few studies which discusses the strategic adoption and the combined use of I4.0 technologies to create more opportunities for product customisation.

This paper investigate how fit uncertainty impacts product return costs in online retailing and how digital product fitting, a pre-sales fitting practice, can reduce fit uncertainty.

The paper analyzes the current performance of a retailer's e-commerce and return operations by estimating costs generated by product returns, including product handling costs, tied-up capital, inventory holding costs, transportation costs, and order-picking costs. The estimated costs were built on 2,229 return transactions from a Scandinavian fashion footwear retailer. A digital product fitting technology was tested with the retailer’s products and resulted in estimations on how such technology could affect product returns.

The cost of a return is approximately 17% of the prime cost. The major cost elements are product handling costs and transportation costs, which together amount to 72% of the total costs. If well calibrated, the fitting technology can cut fit-related return costs by up to 80%. The findings show how customers reacted to the fitting technology: it was unable to verify fit every time, but it serves as a useful and effective support tool for customers when placing orders.

Virtual fit verification using digital product fitting is key to retailers to reduce fit-related returns. Digital product fitting using three-dimensional scanning is more appropriate for some products, but it is unsuitable for products that are difficult to measure and scan.

The paper contributes an empirical estimate of retail supply chain costs associated with fit uncertainty, as well as theoretical understanding of the role of pre-sales fit verification in avoiding product returns.

The purpose of this paper is to analyze the determinants of the performance of regional industrial technology development programs among the regional strategic industrial development program that the central government and Daegu metropolitan city jointly promoted between 2004 and 2012. Specifically, in this research, the authors are trying to identify the effects of R&D capabilities and technical development tasks on technological and managerial performance.

The dependent variables of this study are technical and economic performance. Technical performance, product and process innovation, economic performance, sales and export increases were measured using five-point Likert scales. The authors added the contribution of sales through technology development to economic performance. The independent variable is the company’s R&D capability, measured by the number of R&D staff compared to the average total number of employees from 2004 to 2012. The characteristics of the technology development tasks were measured by technical characteristics, market characteristics and collaborative research types. The technological characteristics were measured by seven factors, including technological change, technical difficulty, potential in commercialization, competition between domestic and foreign competitors, difficulty in introducing overseas technology and the technological gap. Market characteristics were largely divided into complexity, dynamics and competitiveness. The types of collaborative research were divided into whether or not there were collaborative research with the participation of large corporations. The control variables are firm size (number of employees) and firm age. Regression analysis was used to analyze the determinants of performance, and a difference analysis was conducted to determine the effect of collaborative research on performance.

The main determinants of the regional industrial technology development program performance are the characteristics of the technology development task rather than the internal R&D capability; moreover, the technical characteristics, complexity of the developed product market and participation of large corporations had significant effects on R&D capability. The R&D capacity of firms in internal R&D capacity had a significant effect only on the improvement of technology development ability. Therefore, R&D capacity, which is the main determinant of technology innovation, did not have a significant effect on the performance of short-term technology development tasks. Technological change, technological difficulty, competition between domestic and foreign competitors and the technological gap had positive effects on performance, excluding sales contributions. In addition, the complexity of the developed product market such as the diversification of demand, competitive product and sales distribution channels had positive influences on the performance of technology development programs, unlike dynamics and competitiveness. In this study, the authors cannot confirm the effect of collaborative research on the performance of the technology development programs, but they confirmed that collaborative research involving large corporations had a positive influence on performance.

The results of the analysis of the determinants of regional industrial technology development programs suggest some implications in the future evaluation of these regional industrial technology development programs. It is necessary to review the application qualification and merit, advance review of the business plans and confirmation, an examination of the research results and performance of the applicants and a review of the technology and market situation of the project. For this, the authors suggest that the written review from the relevant technical experts be submitted to the evaluation committees. Also, when establishing regional industrial development programs, they should be evaluated thoroughly, including detailed information and contents about the technical and market characteristics of the local industry.

This research is one of the first to investigate the achievements of R&D support programs among regional industrial development programs in Korea. The results of this study can substantially contribute to the development and implementation of the R&D support policies of the central and local governments. Furthermore, the findings suggest guidelines for improving the performance of R&D support programs in the future. A theoretical model for enhancing the efficiency of government R&D support programs may be established, and an empirical analysis may be conducted to provide practical and academic implications for further research.

This purpose of this study is to analyze consumer behavior in relation to Google Glass. The study considers the adoption and diffusion of the innovation, aspects related to technological convergence and the theories of utilitarian, hedonic and social value.

This qualitative, exploratory study uses the methodological approach of netnography via passive observation. Data collection was conducted using the social network Reddit over a period of about four months.

Three categories and two subcategories of consumers were found, namely, socially satisfied; socially constrained; and early adopters, divided into enthusiasts and visionaries.

A limitation of this research pertains to the data collected regarding consumption preferences of users and potential adopters. No questions were created, but rather, discussions were selected, from the social network Reddit, that focused on factors pertaining to the theories studied.

The research brings an important insight regarding the launch of new products: to obtain a good market position for new devices, failures or inadequate perceptions that will negatively impact the technology’s dissemination must be minimized.

This study presents social value of technological consumption as a function of the conspicuousness, status and position of users who own devices that differ from those commonly available on the market.

This study reveals which elements exert the greatest influence on intention to consume so-called wearable technology. In particular, it analyzes consumer behavior in relation to Google Glass, evaluating the reasons that were perceived as positive and negative for consumers which blocked the technology launch in the market.

Industry 4.0 (I 4.0) consists of numerous digital technologies applied in organizations strategically to add value to the customer. Different organizations have varying degrees of technological capability and strategic flexibility. This paper aims to explore the relationship between technological capability and strategic flexibility on successful implementation of I 4.0.

A qualitative study using a grounded theory approach is conducted on 34 senior managers from Europe and North America who have implemented I 4.0 participated in this study through a theoretical sampling frame.

This study finds that technological capability and strategic flexibility have an impact on the successful implementation of I 4.0. The study also finds that different dimensions of technological capability also impact I 4.0. The interactive effect of strategic flexibility and technological capability is also noted. The study also develops a framework for successful implementation of I 4.0.

This study can be used by managers while implementing I 4.0 to devise a strategic roadmap for acquiring technological capability with I 4.0 technologies. Besides, it will help the managers to consider the bidirectional relationship between technological capability and strategic flexibility while formulating I 4.0 strategy for successful implementation of I 4.0 in their organizations.

Previous studies have examined the importance of I 4.0 technologies. However, this study extends the previous works by suggesting how technological capability and strategic flexibility can help in the successful implementation of I 4.0.