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1 – 10 of 108Yuanzhu Zhan, Kim Hua Tan and Robert K. Perrons
In today’s rapidly changing business environment, the case for accelerated innovation processes has become increasingly compelling at both a theoretical and practical level. Thus…
Abstract
Purpose
In today’s rapidly changing business environment, the case for accelerated innovation processes has become increasingly compelling at both a theoretical and practical level. Thus, the purpose of this paper is to propose a conceptual framework for accelerated innovation in a data-driven market environment.
Design/methodology/approach
This research is based on a two-step approach. First, a set of propositions concerning the best approaches to accelerated innovation are put forward. Then it offers qualitative evidence from five case studies involving world-leading firms, and explains how innovation can be accelerated in different kinds of data-driven environments.
Findings
The key sets of factors for accelerated innovation are: collateral structure; customer involvement; and ecosystem of innovation. The proposed framework enables firms to find ways to innovate – specifically, to make product innovation faster and less costly.
Research limitations/implications
The findings from this research focus on high-tech industries in China. Using several specific innovation projects to represent accelerated innovation could raise the problem of the reliability and validity of the research findings. Additional research will probably be required to adapt the proposed framework to accommodate the cultural nuances of other countries and business environments.
Practical implications
The study is intended as a framework for managers to apply their resources to conduct product innovation in a fast and effective way. It developed six propositions about how, specifically, data analytics and ICTs can contribute to accelerated innovation.
Originality/value
The research shows that firms could harvest external knowledge and import ideas across organisational boundaries. An accelerated innovation framework is characterised by a multidimensional process involving intelligence efforts, relentless data collection and flexible working relationships with team members.
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Navid Mohammadi, Nader Seyyedamiri and Saeed Heshmati
The purpose of this study/paper is conducting a Systematic mapping review, as a systematic literature review method for reviewing the literature of new product development by…
Abstract
Purpose
The purpose of this study/paper is conducting a Systematic mapping review, as a systematic literature review method for reviewing the literature of new product development by textmining and mapping the results of this review.
Design/methodology/approach
This research has been conducted with the aim of systematically reviewing the literature on the field of design and development of products based on textual data. This research wants to know, how text data and text mining methods, can use for the design and development of new products.
Findings
This review finds out what are the most popular algorithms in this field? What are the most popular areas in using these approaches? What types of data are used in this area? What software is used in this regard? And what are the research gaps in this area?
Originality/value
The contribution of this review is creating a macro and comprehensive map for research in this field of study from various aspects and identifying the pros and cons of this field of study by systematic mapping review.
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Manoj Palsodkar, Gunjan Yadav and Madhukar R. Nagare
The market's intense competition, the unpredictability of customer demands and technological advancements are compelling organizations to adopt new approaches, such as agile new…
Abstract
Purpose
The market's intense competition, the unpredictability of customer demands and technological advancements are compelling organizations to adopt new approaches, such as agile new product development (ANPD), which enables the introduction of new products to the market in a short span. The existing ANPD literature review articles are lacking in portraying recent developments, potential fields of adoption and the significance of ANPD in organizational development. The primary goal of this article is to investigate emerging aspects, current trends and conduct a meta-analysis using a systematic review of 177 ANPD articles published in peer-reviewed journals between 1998 and 2020.
Design/methodology/approach
The articles were categorized based on their year of publication, publishers, journals, authors, countries, universities, most cited articles, etc. The authors attempted to identify top journals, authors, most cited articles, enablers, barriers, performance metrics, etc. in the ANPD domain through the presented study.
Findings
The major themes of research articles, gaps and future trends are identified to assist academicians and ANPD practitioners. This study will benefit ANPD professionals by providing them with information on available literature and current ANPD trends.
Originality/value
Through meta-analysis, this study is one of the unique attempt to categorize ANPD articles to identify research gaps and highlight future research trends. A distinguishing feature of the presented study is the identification of active journals, publishers and authors, as well as enablers, barriers and performance metrics.
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Hannu Hannila, Joni Koskinen, Janne Harkonen and Harri Haapasalo
The purpose of this paper is to analyse current challenges and to articulate the preconditions for data-driven, fact-based product portfolio management (PPM) based on commercial…
Abstract
Purpose
The purpose of this paper is to analyse current challenges and to articulate the preconditions for data-driven, fact-based product portfolio management (PPM) based on commercial and technical product structures, critical business processes, corporate business IT and company data assets. Here, data assets were classified from a PPM perspective in terms of (product/customer/supplier) master data, transaction data and Internet of Things data. The study also addresses the supporting role of corporate-level data governance.
Design/methodology/approach
The study combines a literature review and qualitative analysis of empirical data collected from eight international companies of varying size.
Findings
Companies’ current inability to analyse products effectively based on existing data is surprising. The present findings identify a number of preconditions for data-driven, fact-based PPM, including mutual understanding of company products (to establish a consistent commercial and technical product structure), product classification as strategic, supportive or non-strategic (to link commercial and technical product structures with product strategy) and a holistic, corporate-level data model for adjusting the company’s business IT (to support product portfolio visualisation).
Practical implications
The findings provide a logical and empirical basis for fact-based, product-level analysis of product profitability and analysis of the product portfolio over the product life cycle, supporting a data-driven approach to the optimisation of commercial and technical product structure, business IT systems and company product strategy. As a virtual representation of reality, the company data model facilitates product visualisation. The findings are of great practical value, as they demonstrate the significance of corporate-level data assets, data governance and business-critical data for managing a company’s products and portfolio.
Originality/value
The study contributes to the existing literature by specifying the preconditions for data-driven, fact-based PPM as a basis for product-level analysis and decision making, emphasising the role of company data assets and clarifying the links between business processes, information systems and data assets for PPM.
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Yuanzhu Zhan, Kim Hua Tan, Leanne Chung, Lujie Chen and Xinjie Xing
The main purpose of this paper is to investigate how social media can provide important platforms to facilitate organisational learning and innovation in new product development …
Abstract
Purpose
The main purpose of this paper is to investigate how social media can provide important platforms to facilitate organisational learning and innovation in new product development (NPD) process.
Design/methodology/approach
Using a multiple case-study approach, this study assesses qualitative data collected via 56 interviews from 13 world-leading Chinese companies in the high-technology industry.
Findings
The study identified three distinct types of organisational learning mechanisms for firms to extract potential innovation inherent in social media. It further determined various organisational enablers that facilitate the connections between these mechanisms and NPD performance.
Research limitations/implications
This research contributes to the emerging literature on digital product development and organisational learning. The cases were conducted in the Chinese context, hence, the results may not be fully generalisable to other organisations, industries and countries without appropriate re-contextualisation.
Practical implications
The empirical evidence showcases the various mechanisms adopted by managers in different NPD phases. It identifies several technological and organisational adaptations that managers can apply to smartly scale their social presence and facilitate NPD.
Originality/value
Despite the exponential growth of social media use in identifying and interacting with external stakeholders, managerial practice and academic research have paid little attention to how social media can be leveraged for NPD. The value of this research comes from applying a qualitative method to gain in-depth insights into the mechanisms for leveraging social media to facilitate innovation in NPD.
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Asmita Verma and Anjula Gurtoo
The paper aims to review rules and policy guidelines worldwide around non-personal data (NPD) and evaluate the policies on criteria that allow for the use of data for economic and…
Abstract
Purpose
The paper aims to review rules and policy guidelines worldwide around non-personal data (NPD) and evaluate the policies on criteria that allow for the use of data for economic and social good. A review related to diverse policy approaches of various countries remains a research gap, and hence the analysis in the paper is designed with the intention of developing a research framework and providing policy gaps for further exploration.
Design/methodology/approach
A systematic review of academic and non-academic literature on theoretical foundations, applications of NPD for economic and social good and NPD policies and regulations was conducted to identify the evaluation criteria. A total of 32 dimensions got identified for evaluation. As second step, content analysis was used for evaluation. A total of 13 documents from 6 countries and 1 geographical region were identified for evaluation. The documents were evaluated based on the 32 dimensions spread across 5 domains that facilitate data access and sharing for economic and societal benefit.
Findings
The analysis highlights three distinct emerging perspectives on data exchange: most policy and regulatory documents acknowledge the importance of identifying different types of NPD and accordingly describing the distinct roles and responsibilities of data actors for leveraging the data; the policy and regulatory frameworks clearly focus on increasing business opportunities, data sharing cooperation and innovation; and findings also demonstrate certain gaps in the policy frameworks such as a more comprehensive discussion on data access and sharing mechanisms, particularly data sandboxes and open data, and concrete norms and rigorous standards regarding accountability, transparency, ownership and confidentiality. Furthermore, policies and regulations may include appropriate incentive structures for data providers and users to ensure unhindered and sustainable access to data for the common good.
Originality/value
To the best of the authors’ knowledge, this paper represents one of the first research contributions evaluating global data policies focused on NPD in the context of its increasing use as a public good. The paper first identifies evaluation criteria for the analysis on public and social good, and, thus, provides a conceptual framework for future research. Additionally, the analysis identifies the broad domains of policy analysis on social and public good for data economics.
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Aris Georgiou, George Haritos, Moyra Fowler and Yasmin Imani
The purpose of this paper is to focus on how the concept design stage of a powertrain system can be improved by using a purely objective driven approach in selecting a final…
Abstract
Purpose
The purpose of this paper is to focus on how the concept design stage of a powertrain system can be improved by using a purely objective driven approach in selecting a final concept design to progress further. This research investigation will examine the development of a novel test-bed to assist in the selection of powertrain technologies during the concept design phase at Ford Motor Company Ltd, serving as the main contribution to knowledge.
Design/methodology/approach
The objectives of this research were achieved by carrying out a literature review of external published work related to concept design evaluation methods within product development and value engineering techniques. Empirical studies were conducted with a supporting case study used to test the application of a new test-bed to improve the concept design decision process.
Findings
A quantitative new tool “Product Optimisation Value Engineering” (PROVEN) is presented to critically assess new and evolving powertrain technologies at the concept design phase.
Research limitations/implications
This research improves the concept design selection process, hence increasing the product value to the customer.
Practical implications
The new test-bed “PROVEN” incorporates a data-driven objective approach to assist in assessing concept design alternatives in providing the net value in terms of function and cost as perceived by the customer.
Originality/value
A mathematical new test-bed that incorporates a highly adaptable, data-driven and multi-attribute value approach to product specification and conceptual design is developed, novel to the automotive concept design process. This will create a substantially optimised product offering to the market, reducing overall development costs while achieving customer satisfaction. The new tool has the ability to define a technology value map to assess multiple technical options as a function of its attributes, whose precise values can be determined at a given cost.
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Although the business model (BM) has become a top priority in management research, existing literature still offers a confusing and partial picture about how to leverage BM…
Abstract
Purpose
Although the business model (BM) has become a top priority in management research, existing literature still offers a confusing and partial picture about how to leverage BM designs for new product development (NPD) because of two limitations. First, research has paid little attention to different BM designs' effects on NPD performance. Second, few empirical studies have examined the moderating roles of firms' learning capabilities, such as big data analytics capabilities (BDA capabilities). This study aims to investigate the effects of BM novelty design and BM efficiency design on NPD performance and the ways in which BDA capabilities moderate these effects.
Design/methodology/approach
A literature review provides the model and hypotheses. Using a sample of 208 Chinese firms, the authors conducted an empirical test following multiple regression analysis.
Findings
The results demonstrate that BM novelty design has a positive effect on NPD performance while BM efficiency design takes the form of an inverted U-shape. Moreover, BDA capabilities (i.e. BDA technology capability and BDA management capability) have complicated moderating effects on BM novelty design- and BM efficiency design-NPD performance relationships.
Research limitations/implications
The results may be affected by both the context (solely in China) and type (cross-sectional) of the data set. This study has explored the moderating effects of BDA capabilities, further studies considering other significant practices such as social media usage, could yield richer insights that would help validate the results of this study.
Practical implications
First, we suggest that managers should be explicitly aware of the different impacts of BM novelty design and BM efficiency design on NPD performance. Second, this study encourages managers to build relevant BDA capabilities to work with BM designs to improve NPD performance.
Originality/value
This is one of the first studies to investigate BM designs' complicated influences on NPD success and explore BDA capabilities' moderating effects on the BM design-NPD performance linkage.
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R. Dale Wilson and Anna M. Stephens
This study aims to demonstrate how marketing analytics can be used to identify the challenges a B2B company faced in the conversion from a hard-copy print catalog to a digital…
Abstract
Purpose
This study aims to demonstrate how marketing analytics can be used to identify the challenges a B2B company faced in the conversion from a hard-copy print catalog to a digital ordering system. Specifically, an empirical research approach identified the potential issues the company was likely to face in the digitalization of the company’s catalog.
Design/methodology/approach
Using the Qualtrics survey platform, a questionnaire was used to obtain a final sample of 332 customers (a 14.02% response rate) on a variety of issues related to the transition from the company’s current printed catalog to a digital catalog ordering system. A variety of data analysis procedures were used to gain insight and highlight potential issues in the move to a digital format.
Findings
A variety of potential stumbling blocks were identified that suggest the company should move forward with caution. The data analysis was used to suggest areas that needed to be emphasized in the rollout of the new digital ordering system.
Research limitations/implications
Like all marketing research, this application is limited by the methods used and the data generated by this study. Its implications suggest the potential use of marketing research before an important change in a B2B company’s marketing approach.
Practical implications
This paper provides an approach that can be used by firms considering a change to digitize key components of their marketing assets.
Originality/value
The research contributes to the B2B marketing literature by demonstrating how data-driven marketing analytics can be used to identify potential issues prior to the development of a new digital marketing approach used by B2B firms.
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Sandeep Jagtap and Linh Nguyen Khanh Duong
Recently, the concept of big data (BD) has evolved and started to play an essential role in the advancement of new product development (NPD) in various sectors contributing to…
Abstract
Purpose
Recently, the concept of big data (BD) has evolved and started to play an essential role in the advancement of new product development (NPD) in various sectors contributing to value creation, idea generation and competitive advantage. However, limited research has been done on how the food industry can exploit BD to improve the processes involved in NPD. The purpose of this paper is to understand the use of BD in new food product development. It helps to find relevant information and integrate sustainability to the early stages of the NPD process in the food industry.
Design/methodology/approach
This research illustrates a case study of a beverage company wherein they used BD analytics to support their NPD team to launch a two-litre lemonade drink in the market for their retailer with less than 5 g sugar per 100 ml in the shortest possible time.
Findings
The use of BD helps to reduce NPD costs and time without affecting the taste and on par with competitor’s products.
Originality/value
The research can support NPD professionals through the application of BD analytics to bring products at lower costs to the market as quickly as possible.
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