Characteristics of Lead Users in Different Stages of the New Product Development Process: A Systematic Review in the Context of Open Innovation

Abstract

Despite the promising ideas of lead users, the success rate of the open innovation process remains low if no proper personal characteristics are attached to the external contributor. The knowledge about the essential characteristic elements of lead users is crucial to select the right lead users in the early stage of the NPD. By filling the research gap, we performed a systematic literature review about the required personal characteristics of lead users. The resulting 45 studies demonstrated that diverse characteristics are required in different stages of an NDP which vary in the consumer and industrial context. According to our research results, we made a contribution to the theory by extending the lead user method in the form of a partial theory. We also found that in the case of incremental innovations, companies apply their technical knowledge and do not require additional expertise from users, while in the case of radical innovations, firms only involve external users with high technological competencies in the development stage of the NDP. We identified similarities and differences of the required lead users’ personal characteristics in the consumer and industrial contexts. Thus, our study provides a better awareness for business leaders on the selection of lead users for their NPD process, reducing the time-to-market ratio of the product and increasing profit.

1. Introduction

Open innovation supports corporate growth and profitability. Firms are increasingly opening their boundaries and applying various methods to identify user innovations [1] and tap users’ product knowledge and experience [2,3]. Successfully innovating firms involve users [4,5], customers [6] and patients [7] in the “fuzzy front end” of their new product development (NPD). Ref. [8] states that average users are not suitable for developing novel product attributes because they cannot accurately determine future market needs. Only leading-edge users with real-life usage experience can provide accurate information on the needs for product development. Quality information from lead users [9] and their systematic design freedom [10] results in better product development. von Hippel first defined the term lead user, then assigned two main attributes to identify them: “lead users face needs that will be general in a marketplace—but face them months or years before the bulk of that marketplace encounters them, and lead users are positioned to benefit significantly by obtaining a solution to those needs” [8] (p. 13). The high expected benefit and the superior trend position are also strong predictors for co-creation [11].

The lead-user method aims to identify and involve lead users to the NPD process as they are “at the leading edge of each identified trend in terms of related new products and process needs” and they “expect to obtain a relatively high ‘net benefit’ from solutions to those needs” [8] (p. 798). All later adoptions of the lead user method contain these two crucial attributes of lead users [12,13,14,15]. The adaption of the lead user method by [16] consists of the following four steps: 1. start of the lead user process, 2. identification of needs and market trends, 3. identification of the lead user, 4. concept design and the start of co-creation. According to scholars, it is challenging to determinate lead users in the fuzzy front end of the NPD process [17,18,19] even with the existence of multiple identification methods [20,21,22].

While the lead-user method is suitable for the identification of lead users based on the two main attributes of ‘ahead of market trend’ and ‘high expected benefit’, it does not consider explicitly the personal characteristics elements of lead users, such as users’ knowledge, motivation, skills, behavior, experience, betweenness centrality, attractiveness, etc. Studies emphasize that the lead users’ personal characteristics are crucial for successful co-creation. According to [23], the contribution of individuals to the co-operation process varies strongly; therefore, the proper selection of lead users plays a critical role. This is in line with the findings of [24], which states that the characteristics of users differ significantly from the user type, typically involved in conventional research. Scholars emphasize the importance of selecting the right user profiles for the development process [25,26,27]. The authors [28] (p. 13) highlight the role of ‘the human factor’ and state that the synergy in innovation “can only be achieved if the right number of the right people are prepared to collaborate with each other” (ibid).

An increasing number of studies investigate lead users’ personal characteristics. Ref. [24] underlines the importance of imagination capabilities, openness to new technologies, high level of expertise and technological competencies. According to [29], consumer knowledge, use experience, locus of control and innovativeness are important antecedents of lead userness. Refs. [17,30] highlight the importance of “local” (tacit knowledge) information. Ref. [31] finds a positive impact on willingness, task motivation, creativity components, and relevant product knowledge. Ref. [32] states that individuals’ creativity and personality play an important role in the determination of lead userness. Ref. [33] finds that managers shall pay attention to the selection of the right users for idea generation of an innovation process. Ref. [34] emphasizes that improper customers may appear to offer benefits as experience sharing and improvement suggestions; however, their value is misleading due to the missing vital personal characteristics. Ref. [35] describes the case of failed innovation by ostensible users with a lack of essential characteristics.

Studies show that co-creation is an emerging phenomenon of contribution where customers are the central and essential part of the NPD process [36]. The participation of users has become crucial to realize successful innovation [37]. This kind of co-creation is different from the broader understanding of co-creation, which refers to co-creation experiences that includes the whole interaction between the customer and the firm, and it focuses on “creating an experience environment in which consumers can have active dialogue and co-construct personalized experience” [38] (p. 8). In our case, co-creation is also different from customer involvement to allow for a single point of idea exchange [23]. Co-creation is when lead users actively participate in all phases of the NPD, including idea generation, concept formulation, product development and test, market diffusion and post-launch activities [39].

As the personal characteristics of lead users have a high impact on the success of the open innovation process, the clear understanding of the required personal characteristics’ elements at different stages of the NDP is therefore crucial for managers to select the proper lead users for their NDP process. The relevance of the problem is judged by the evidence that managers aim to select the right lead users for their NPD depending on the level of lead user involvement in the NPD. In the case of high-level involvement, decision makers aim to reduce the gap of different professional backgrounds, different points of view between external contributors (lead users) and internal employees (engineers, product owners, etc.). The knowledge about the lead user characteristics in different stages of the NPD is relevant for making the right decision during the selection process of lead users.

Scientific articles usually investigate only one or some personal characteristic elements of lead users in a dedicated market context (consumer or industrial). Insights into what is important at different stages of the NPD is very scarce. Although these publications are of great scientific value, we found no study which comprehensively reviews the published peer-reviewed papers related to the personal characteristics of lead users in different stages of the NPD process. In order to fulfil this research gap, we carried out a systematic literature review (SLR) and report the findings in our study.

The authors defined three aims of the systematic literature review (SLR). The first goal is to create a narrow research question and systematically search, analyze and synthesize research results of the published literature between 2000 and 2020, taking account of the value and accuracy of the studies. The second aim is to report findings at different stages of the NPD process separated into consumer and industrial contexts, while the third one is to identify research gaps for further research, which requires additional exploration and investigation. To reach the above objectives, the following research question is formulated:

RQ: What personal characteristics of lead users’ managers need to consider in the selection process of lead users by considering each stage of the NPD process and the differences between the consumer and industrial segments?

We considered the lead user method as a basic concept to identify and involve lead users in the NPD process. We have assumed the missing link of the step of ‘selection of lead users based on their personal characteristics’ in the lead-user method between the steps of ‘identification of lead user’ and ‘start of co-creation’ (see Figure 1). Step IV shows the clear focus of the SLR and determines the contribution of our research results to the lead-user method.

The research is also driven by the intrinsic motivation of the authors as one of them spent more than a decade in the high-tech industry as a manager and found that users’ brilliant ideas are valueless and no significant commercial success could be achieved if no proper personal characteristics are attached to the lead users during the open innovation process.

To perform our work effectively, we followed appropriate rigor and consistency and used an explicit and reproducible method. In the study, the authors followed the guidelines proposed by Refs. [40,41,42].

At this point of the study, we would like to make a note about the applied terminology of “customers” and “users”. Both expressions are used with identical value. The difference between them is the context in which they are used. In the industrial context, end users (named “users”) of a product use the product directly without making a purchasing decision, while users in the consumer context (called “customers”) use a product directly along with making also a purchasing decision. We use the term “user” in the industrial context and the term “customer” in the consumer context with an identical value. The following section describes the literature review method, including the assessment criteria, search strategy, study selection process and quality assessment.

The systematic literature review consists of the following sub-elements: 1. identifying the review questions, 2. formulating the research method, 3. defining the inclusion and exclusion criteria, 4. implementing quality assessment and 4. synthesing the evidence to answer the research questions.

2. The Review Method

The review protocol describes and identifies the method to be applied to carry out a systematic literature review. The review protocol is an important step to minimize the possibility of researcher bias and avoid an analysis driven by the researcher’s expectations [42], and additionally to avoid fuzzy input that tends to lead to fuzzy answers. The review protocol contains all elements of the review method, including the research background and research question, study selection criteria, search strategy, quality assessment, extraction, and synthesis of the primary studies. Taking these factors as departure, our study reviews the research question and the research background as described above in the previous sections of this paper. The following sub-sections of our study contains the remaining listed elements of the review method.

2.1. Inclusion and Exclusion Criteria

The inclusion and exclusion criteria ensure that all selected primary research is pertinent and relevant to the study. The aim of our literature review is to understand the personal characteristics of the lead user, which enables a successful contribution to the co-creation process. Related to this stated research question, the review contains data from journal articles and conference proceedings available in full text, published in English in the identified databases between 2000 and 2020 in the domain of open innovation. The authors have excluded research articles with content unavailable in full text, research published outside of the identified time frame, research without proper description of data sources and methodologies, studies containing no relevant research results about the lead users’ personal characteristics, and papers containing only secondary research results.

Table 1. Inclusion and exclusion criteria.

Inclusion criteria:	Available in full text
	Published between 2000 and 2020
	Written in English
	Related to the research question
	Within the searched domain of open innovation
	Published in the selected databases
Exclusion criteria:	Full text unavailable in electronic form
	Outside of the search timeframe
	Research without the description of data sources and methodology
	No information about lead user characteristics
	Papers with only secondary research results

covers all criteria for the literature review:

2.2. Search Strategy

The search strategy involves both automatic and manual searches to explore a broader perspective of lead-user characteristics. The automatic search was an electronic search based on the defined keywords to address the research question of the SLR. Following the recommendation by [42], we conducted firstly the automated search for primary study references and secondly the manual search. Four online scientific databases were selected as the main sources for the review: ScienceDirect, JSTOR, Scopus and Whiley Online Library. These databases provided the most relevant information for the domain related lead user’s characteristics. The used keyword string with the Boolean applied operators was: “lead-user” and “characteristics” and “new product development” and “innovation”. Although the word “co-creation” would theoretically lead to more accurate search results, the authors decided to exclude this keyword from the search string as the search had filtered out the relevant studies. After the first stage of the search process, we applied the manual search and utilized the forward and backward search process to track the references of the primary studies through manual reference scanning, which is the so-called “snowballing” method [43]. This process ensured a relatively complete systematic search, even though the primary search had not resulted in identifying relevant articles. Through the backward search, we manually scanned all the references of the current paper to find relevant studies which had not been found by the automatic search. The forward search found papers which confirmed, applied, extended, and improved the results of the referenced study. We used the Mendeley application for sorting all primarily and manually searched-for studies and removed duplicate studies.

The authors followed the review guidelines recommended by [42], which consist of three major parts, including planning, conducting and reporting the review. These stages consist of sub-elements, including 1. formulating the review question, 2. identifying the research method, 3. creating the inclusion and exclusion criteria, 4. performing quality assessment, and 5. synthesing the evidence to answer the research question. The backward and forward search and automatic search ensure that the systematic literature review is the relatively complete processing of the relevant literature [43]. The flow diagram (see Figure 2) presents both automatic and manual searches as well as the selection process with the search results.

2.3. Study Selection Process

The automatic search process resulted in 488 papers by utilizing the defined keywords. Four papers were found as duplicates, and they were removed by using the Mendeley application. The exclusion criteria were applied to the remaining 462 papers focusing on the title, the abstract and the keywords of the papers. The aim of this step was to classify studies accurately to eliminate the ones not in sync with the research question. The process led to 80 studies remaining. The initial automatic search brought about many papers unrelated to the research question. As recommended by [44], the authors maintained a list of excluded papers at this stage of the selection process. The next step involved reading the remaining studies to apply the inclusion/exclusion criteria, which culminated in 47 papers. Applying the manual and snowballing search methods on Google Scholar and utilizing the quality assessment led to 45 relevant studies.

2.4. Quality Assessment

The authors used a generic set of questions to evaluate the quality of each selected primary paper. This refers to a process of weighting the importance of each study when the results and the findings of selected primary studies are interpreted [44]. The authors conducted a quality assessment (QA) of the selected primary studies to fulfil the quality and accuracy criteria. Five QA criteria were formulated as

Table 2. List of the quality assessment criteria.

QA1:	Does the research investigate users’ characteristics?
QA2:	Does the type of cooperation refer to co-creation?
QA3:	Is the market domain accurately defined?
QA4:	Is the research about new product development?
QA5:	Are the research methodology and results accurately described?

shows.

The quality assessment questions were evaluated on each primary study to strengthen the researchers’ confidence about the overall quality of the selected papers.

Table 3. Results of the paper selection process.

Results of the Study Selection Process	Initial Results	Relevant Studies
ScienceDirect	291	16
Scopus	12	0
JSTOR	39	2
Whiley Online Library	146	18
Google Scholar (second stage)	-	9
Summary:	488	45

shows the results of the QA process.

The papers were graded by “high”, “medium” and “low” quality rankings. If the paper satisfied the criterion, then it was given a score of 1. If the paper partially satisfied the criterion, it was given a score of 0.5. If the paper did not meet the criterion, it was given a score of 0 [45]. According to the QA criteria and scoring process, the highest possible score is 5 (5 × 1) and the lowest possible is 0 (5 × 0). Studies scored between 4 and 5 were considered as high-quality papers, between 3.0 and 3.5 as medium quality and papers with a score of 2.5 as a low-quality paper. We identified nine low-quality papers (20%), seven medium-quality studies (16%) and 29 high-quality research articles (64%). QA ratings of each paper are listed in

Table 4. Quality Assessment scores of primary studies.

SID	QA1	QA2	QA3	QA4	QA5	SUM	SID	QA1	QA2	QA3	QA4	QA5	SUM
S1	0.5	0	1	0.5	0.5	2.5	S24	0.5	0.5	1	0.5	1	3.5
S2	1	0	0.5	1	0	2.5	S25	0.5	0.5	1	0.5	1	3.5
S3	0.5	1	0	0	1	2.5	S26	1	0.5	1	0.5	1	4
S4	1	1	1	1	1	5	S27	1	0	1	0.5	1	3.5
S5	1	0.5	1	1	1	4.5	S28	0.5	1	1	1	1	4.5
S6	1	0.5	1	0.5	1	4	S29	1	0.5	1	0.5	1	4
S7	1	1	1	1	1	5	S30	1	0.5	1	0.5	1	4
S8	0.5	0.5	0.5	0.5	1	3	S31	1	1	1	1	1	5
S9	1	0.5	1	0.5	1	4	S32	1	1	1	0.5	1	4.5
S10	0.5	0.5	0.5	0	1	2.5	S33	0	0.5	1	0	1	2.5
S11	1	1	1	1	1	5	S34	0.5	0.5	0.5	0.5	0.5	2.5
S12	1	0.5	0.5	1	1	4	S35	1	1	1	1	1	5
S13	1	0.5	1	0.5	1	4	S36	1	0.5	1	0.5	1	4
S14	1	0.5	0.5	1	1	4	S37	0.5	1	1	0.5	1	4
S15	1	1	1	1	1	5	S38	1	1	0.5	0.5	1	4
S16	1	0.5	1	0.5	1	4	S39	1	0.5	0	0.5	0.5	2.5
S17	1	1	1	1	1	5	S40	1	0.5	1	1	1	4.5
S18	1	0.5	1	0.5	1	4	S41	1	1	0.5	1	1	4.5
S19	0.5	0	1	0	1	2.5	S42	1	0	0	1	1	3
S20	0.5	0.5	1	0.5	1	3.5	S43	0	0.5	1	0.5	1	3
S21	1	1	1	1	1	5	S44	1	0	1	1	1	4
S22	1	0.5	1	0.5	1	4	S45	1	0.5	1	0.5	1	4
S23	1	0	0.5	0	1	2.5

.

2.5. Data Extraction and Synthesis of SLR

The data extraction form (Appendix A) accurately records all the information that the researchers have obtained from the primary 45 studies. To reduce the chance of bias, the data extraction form has been defined and it includes the following columns: study ID, title and authors, year of publication, context of the research, key findings, used methodology, countries and regions covered by the research, type of paper, data provider of the study, number of samples and the journal name (

Table 5. Data extraction for primary studies.

Study ID:	Unique identifier of the study
Title and Authors:	The title and name of the authors of the study
Year:	The year of publication (between 2000 and 2020)
Context:	Identification of the product field (consumer, industrial, mixed, not available)
Key Findings:	The key findings of the paper
Methodology:	The used methodology in the research (quantitative, qualitative, mix)
Country:	The name of the countries covered by the research
Type:	The type of the paper (journal article, conference proceeding, book chapter)
Data Provider:	Name of the source the study was retrieved from
Number of Samples:	Number of samples used in the research
Journal Name:	Name of the journal the study was published in

).

Following the systematic review, 45 papers as primary studies were finally selected that had been published within the investigated research field.

3. Research Results

The review comprised 44 journal articles and one conference proceeding which was assessed as a high-quality paper. Multiple methodologies, i.e., qualitative, quantitative, and mixed ones, were applied. Out of the total 45 studies, 26 papers (58%) used quantitative methodology, 18 (40%) utilized qualitative methodology and one study (2%) employed mixed methodology.

Figure 3 shows the chronological distribution of the primary studies. The trendline indicates the increasing number of relevant studies related to the research domain of the personal characteristics of lead users.

The SLR resulted in 33 studies concerning the consumer context and 12 studies regarding the industrial domain.

Table 6. The name and ranking of the journals and the number of studies retrieved.

Name of the Journal	Ranking	Number of Studies
Creativity and Innovation Management	Q1	8
Journal of Product Innovation Management	Q1	6
R&D Management	Q1	4
Research Policy	Q1	4
Journal of Business Research	Q1	3
Journal of Engineering and Technology Management	Q1	3
Technovation	Q1	3
Information and Management	Q1	2
Management Science	Q1	2
Organization Science	Q1	2
California Management Review	Q1	1
European Journal of Management and Business Economics	Q2	1
International Journal of Innovation Management	Q2	1
Journal of Management Information Systems	Q1	1
Journal of Marketing Research	Q1	1
Marketing Letters	Q1	1
Technological Forecasting & Social Change	Q1	1

shows the journal names and rankings (source: www.scimagojr.com, accessed on 22 December 2021) of the primary studies, indicating the number of studies retrieved from the journal.

The new product development process is significantly different in the consumer and the industrial domain [27,46]. Considering this fact, the authors systematically distinguished the research contexts and separated the elements of personal characteristics in each stage of the NPD process. The characteristic elements of the lead users are shown in

Table 7. Lead user personal characteristics in consumer and industrial context.

Stages of the NPD Process	References (Consumer Context)	Consumer Context	Both	Industrial Context	References (Industrial Context)
Development and test				technical expertise (positive impact)	[24,47]
	[23,48]		willingness to experiment and test		[24,47]
				technical expertise (negative impact)	[27]
				tolerance for ambiguity	[24,47]
Concept Development	[49]	optimism
	[49]	openness to new experience		openness for new technologies	[24,47]
	[49]	verbal and visual processing styles		interdisciplinary know-how	[24,47]
	[50]	high technological reflectiveness		resources of research	[24,51]
Idea Generation	KNOWLEDGE AND EXPERIENCE
	[17]		prior knowledge and experience		[47,52,53,54]
	[30,55]		need and solution knowledge		[24]
	[29,31,32]		product knowledge, use experience		[24,51,52,53]
	[17,33,56]		technical knowledge		[24,57]
	MOTIVATION AND WILLINGNESS
	[23]		intrinsic motivation		[24,47,52]
	[58]	experienced empowerment		entrepreneurial mindset
					[47]
	[31]	willingness to share ideas		motivation induced by problem	[24]
	[51]	willingness to collaborate
	[31]	motivation driven by excitement
	[51]	brand identity
	CREATIVITY AND SKILLS
	[29,32,49]		divergent thinking style		[24]
	[23,32,49]	creativity relevant skills		imagination capabilities	[24]
	[59,60]	betweenness centrality
	[60]	age and cognitive capacity
	BEHAVIOUR AND ATTITUDES
	[34]	solution-oriented behaviour		financial attractiveness	[27]
	[34]	attention to other’s idea		trustworthiness, credibility	[57,58]
	[61]	early adaption mindset		personal level of interaction	[24,27]
				closeness of relationship	[27]

. The following sub-sections will provide insights on the personal characteristics of lead users in the subsequent stages of the NPD process: 1. idea generation; 2. concept generation and 3. prototype development and testino by answering the research question.

The length of the sub-sections is decreasing because of the following reasons. Firstly, firms involve lead users mainly in the fuzzy front end of the NDP process; therefore, scholars discuss mainly this stage of the NDP. Secondly, in the case of incremental innovations, firms do not require additional expertise from users as they apply their own technical expertise in higher stages of the NDP. In the case of radical innovations, companies involve users only with advanced technological skills in the development stage of the NDP. The number of capable users in higher stages of the NPD is decreasing as the higher levels require additional personal characteristics and they are more challenging to fulfil.

3.1. Idea Generation Stage

3.1.1. Knowledge and Experience

Refs. [24,30] emphasize the importance of the users’ prior technical knowledge, experience and skills as these elements determine the type of idea and the solution the user will develop. Users utilize their own “local” (tacit) stock of need and solution knowledge to develop innovative ideas and products. This repertoire is in line with the statement of [54], which argues that the discovery of a certain innovation opportunity is driven by the user’s prior education, knowledge and work experience. Ref. [24] highlights the importance of in-depth professional knowledge and ‘need knowledge’ of medical surgeons as a crucial basis for innovative idea generation and solutions that meet specific needs.

This type of knowledge gained through experience, experimentation, and extensive learning is tacit; therefore, it is “sticky”, difficult and costly to transfer to manufacturers [17,24,32,62]. Consequently, this may explain the reason why users develop radically new ideas instead of manufacturing firms that are more focused on incremental improvements [24]. Ref. [55] compares internal and external lead users and found that employees who possess ‘need knowledge’ are able to take advantage of the direct access to the organisation knowledge to work out their solution and they are more creative than an employee who lacks ‘need-knowledge’. The same author additionally states that creativity-enhancing knowledge schemas (e.g., solution knowledge) and creativity-hindering knowledge schemas provided by a company may contain knowledge that increases the resistance to change. The same study also highlights that internal user ideas are easier to realize, while external user’s ideas have maximum novelty, user value, and market potential.

Multiple studies find a positive effect of use-experience and product-related knowledge on the innovation activities of the users [17,29,31,51,52,53]. Ref. [33] emphasizes that technically savvy users are more likely to generate technically feasible ideas, while technologically innovative customers tend to provide radical or new product ideas. According to [57], the technical innovativeness of customers increases the intention of firms to involve them in the early stages of the NPD process.

3.1.2. Motivation and Willingness

According to [23], a certain level of interest and task motivation is important in the idea generation phase to come up with new ideas, based on the evidence that creativity is driven by intrinsic motivation [63]. In contrast, Ref. [32] found that intrinsic and extrinsic motivation do not significantly describe the traits of lead users. In the consumer context, Ref. [31] examined the proportion of motivation-driven factors and found that 20% of the innovations are “need-driven” and 80% are “excitement-driven”. The “need-driven” innovation is triggered by the perception of needs not yet fulfilled by the existing products on the market, while the “excitement-driven” innovators develop new ideas because of enjoyment, fun and pleasure, and less due to the desired outcome. This study also claims that community members are willing to share their innovative ideas with manufacturing firms free of charge. Ref. [51] expresses that willingness to collaborate and strategic alignment with brand identity are crucial characteristics of the users’ innovativeness.

In the industrial context, Ref. [52] found intrinsic motivation as the main characteristic of lead users. Ref. [47] states that in terms of radical innovations in the medical domain, manufacturers are reluctant to invest in NPD, considering the design instabilities that trigger the users’ entrepreneurial mindset to gain direct benefit from the tailored new technologies of their needs. The same authors emphasize that professional users experience difficulties in their daily work and they encounter the limits of conventional technologies, which motivate them to search for more workable solutions (motivation induced by problem). This strong intrinsic motivation supports creative activities [23,63] and enable innovations.

3.1.3. Creativity and Skills

Ref. [23] examines the impact of customer’s creativity components at different stages of the NPD process. They found that users in the idea generation phase need to possess creativity-relevant processes, including extraordinary domain-relevant skills and an appropriate motivation level, heuristics, and work style to create creative ideas, while domain-specific skills have no impact on ideas. This finding was explained by the intention of companies being more interested to find and figure out a problem because they usually have strong abilities to develop and produce new products.

The research conducted by Ref. [60] among children shows that “betweenness centrality” (i.e., the bridging link between different social groups in a network) and age have a significant effect on creativity. Children can create more and better ideas with increasing age and cognitive capacity. According to their study, the favorable network position of children stimulates individuals to utilize the information advantage and to become creative. This is consistent with the research conducted among young adults as lead users [59].

In the industrial context and in the medical domain, Ref. [24] states that high problem pressure is the key source of creative activities. A divergent thinking style is the ability to “think outside of the box” and not being restricted by functional fixedness [32].

The close access to transdisciplinary know-how increases users’ creative capacity [24]. Ref. [29] found that innate innovativeness explains creative achievements, including individuals who break “patterns of accepted modes of thought and actions” [64] (p. 623), and similarly, they “tend to take control in unstructured situations” (ibid) and are resistant to former standards and possess a risk-taking manner. The study also states that locus of control (LOC) [65] is a personal characteristic and a key element of creativity [66]. Moreover, they found that lead users possessing high internal LOC are likely to deal with new usage situations. They leave the solid terrain of the ordinary, usually commit to a difficult risky task and put effort into mastering improvements in existing products.

3.1.4. Behavior and Attitude

Ref. [34] investigated ideators’ online behavior and they found that their value lies in solution-oriented behavior and paying attention to other’s ideas. The solution-oriented behavior is more related to suggesting improvements on existing goods than suggesting ideas. The ideators, who are curious and open to other ideators’ ideas, are more likely to be successful. Lead users with early product adaption behavior are a valuable source of new ideas and additionally, they can successfully fuel the market diffusion process [61].

According to [58], empowered customers are more innovative through a co-creation IT tool, they feel trust and are willing to put effort into making a valuable contribution. Such a tool enables less-skilled customers and lower qualified users to participate in the virtual NPD task.

In the industrial context, Ref. [27] found that close customers and financially attractive customers yield a positive impact to the success of NPD, which relates to their market representation and reputation on the market. Additionally, they state that intensive customer interaction and close customers positively influence the product’s success. In line with this statement, Ref. [24] underlines the importance of personal face-to-face interactions with users to develop and understand the user’s complex and tacit information to be transferred. Ref. [27] found that personal interaction can increase the new product success during the early and late stages of the NPD, while the concept generation stages yield no impact. Appropriate skills for interaction need to be developed in radical innovation projects with respect to the users and firms. Ref. [57] claimed that in the collaboration process, firms require trustworthiness and credibility from customers otherwise they will ignore them.

3.2. Concept Generation Stage

Ref. [49] states that consumer innovativeness correlates positively with personality traits and processing abilities. Such customers, called “emergent nature customers”, possess unique capabilities to envision or imagine how new product concepts might be developed. These unique personality traits and processing abilities support the product concept stage, enhance the ability to process information visually and verbally, and they are open to new experiences, reflection, thinking styles, a high level of creativity and optimism. In contrast, Ref. [67] found that lead users and also average users outperform the “emergent nature customers”.

Ref. [50] states that technologically reflective customers demonstrate benefits in the concept generation and refinement phase. Technologically reflective customers can think about the impact of a product on its user’s society in general.

Ref. [23] finds that domain-specific skills (e.g., factual knowledge of the domain, familiarity, and technical skill) and creativity relevant processes have a lower impact on the concept generation in comparison with the idea generation. The authors also highlighted that task motivation has no impact on the concept development or on the prototype development.

In the industrial context, only a few studies have been found that investigate users’ characteristics in the concept development phase. Ref. [24] defines critical lead user characteristics including imagination capabilities, openness to technologies outside of the certain domain, and close access to an interdisciplinary approach. They all inspire creative thinking to develop state-of-the-art technologies. The availability of resources for research, e.g., time, human resources, and funds, are important individual and contextual factors in this stage of the NPD. Users without a supportive environment and available resources exhibited lower efficiency. Characteristics elements, such as problem-induced motivation, openness, and prior knowledge, play a crucial role at this stage of the new product development as well [24].

3.3. Prototype Development and Testing Stage

A limited number of studies have been found regarding the last stages of the NPD, i.e., prototype development, product development, and the testing stage.

In the consumer domain, Ref. [23] states that at this level of the NPD, the creativity-relevant processes and task motivation have no impact on the contribution of users, while domain-specific skills play an enhanced role in the users’ interest in experiencing and testing new products. Ref. [48] states that the willingness to experiment is crucial at this stage, which is aligned with the ideas of Ref. [24] as well.

In the industrial context, Ref. [24] realized that the characteristics of tolerance for ambiguity are essential to deal with uncertainty between the final output and benefit of the product. The author emphasizes the importance of technological competencies, such as mechanics, electronics, and computer programming, in cases of radical innovations. In contrast with this finding, Ref. [27] concluded that there is a negative performance impact of technically attractive users related to their contribution to the development of mid-range (innovations between minor and radical changes) innovations. They argued that companies rely on their own technical expertise and they shall not expect additional skills from users.

4. Discussion

Based on the above-presented systematic literature review, this paper has provided an overview of lead users’ personal characteristics related to NPD in case of co-creation. Altogether, 45 primary studies were found by performing the automatic and manual search processes, applying inclusion and exclusion criteria, and conducting quality assessment. The selected studies have been organized into two categories, i.e., consumer and industrial contexts, as they provide the key research settings of the studies. The majority of the articles, 73% (33 studies), were related to the consumer context and 27% (12) were to the industrial context. To fulfil the quality and accuracy criteria and strengthen the researchers’ confidence about the overall quality of the selected papers, the authors conducted a quality assessment process related to the primary studies. The assessment process resulted in 64% (29) high-quality papers, 16% (7) medium-quality papers and 20% (9) low-quality papers. To reduce the possibility of bias, the data extraction form has been defined (Appendix A) to record all information accurately that the authors obtained from the primary 45 studies.

To report the findings in a systematic way and provide an answer to the research question, we classified the NPD process into three stages, which are the following: 1. idea generation, 2. concept formulation, and 3. prototype and product development and test stages. We have found that most of the studies focus only on a fuzzy front end of the NPD process, and they discuss the personal characteristics of lead users only in connection with the idea generation stage. A limited number of studies have been found which discuss the characteristics in the later stages of NPD because fewer users are involved in the subsequent stages of the new product development process. The reason is that the number of capable users is decreasing as the higher levels require additional personal characteristics and they are more challenging to fulfil. We summarized the found personal characteristics elements in Figure 4.

We find significant differences in the consumer and industrial segments which shed light on the importance of context separation. This knowledge provides additional information for innovation managers to select the proper lead user for their co-creation process. The perspective of the market contexts provides complementary information and enables us to consider the required personal characteristics of lead users as a two-dimensional system: 1. personal characteristics in different stages of the NPD process and 2. personal characteristics in a dedicated market context. The differences are explained below and summarized in

Table 8. Differences in the consumer and industrial segments.

	Consumer Context	Industrial Context
Type of Users:	hobbyist [29,47,68]	professionals [47,68]
Interaction/Participation	online user communities without face-to-face interaction [68]; application of IT tools for “low skilled users” to involve [58]	high level of personal interaction (face-to-face) [24,53]; the intensity of customer interaction varies in different stages of the NPD process
Motivation:	20% “need-driven” and 80% “excitement-driven” [31], enjoyment of activity [30], experiment-driven [31,73]	induced by needs and problems [24]
Type of Innovation:	incremental [68] improvements, smaller changes [17]; can be characterized by low novelty [71] and lack of users’ knowledge [35].	Radical innovation [24]
Identification of Lead Users Status:	in the beginning of the NPD process [31]	in later phases of the NPD process [24]
Needed Tools:	online tools	no tools
Belonging to Community:	motivates greater involvement and willingness to interact [51]	community membership does not impact willingness to become inventive
Brand Identity/Loyalty	strategic alignment with brand identity [51]	-
Reward:	Free	-
Innovation Capabilities:	Low	well-developed [24,72]
Decision Base:	emotional [35]	rational

.

In the consumer segments, most of the lead users can be described as a hobbyist [29,47,68]. Firms utilize online IT tools to involve “low skilled users” without any face-to-face interaction [58,68]. The minority of lead users’ motivation is “need-driven” and the majority is “excitement-driven” [31] and experiment-driven [31,69] or simply driven by the enjoyment of the activity [30]. The type of innovations refers to incremental innovation [68] improvements, smaller changes [17,70] and can be characterized by low novelty [71]. Lead users can be identified in the early phase of the co-creation process [31]. The community membership and strategic alignment with brand identity have a positive impact on the motivation to interact [51]. Lead users in the consumer segment tend to earn free rewards. The innovation capabilities of lead users remain low, which corresponds to the required skills of firms in the consumer segment in the idea generation phase. According to [35], lead users in the consumer segments decide emotionally.

In the industrial segment, most of the lead users are professionals [47,68]. The co-creation process requires a high level of personal interaction, but its intensity varies in different stages of the NPD process [53]. The motivation of lead users is triggered by needs and problems. Lead users in the industrial segments produce mostly radical innovations. The identification of lead users can happen in the later phase of the NDP process as lead users innovate during their everyday work [24]. Firms apply no tools to involve lead users in the co-creation. The innovation capabilities of lead users are well developed [72]. The decision base of lead users is mainly rational.

5. Contribution, Implications and Future Research

In conclusion, we state that the personal characteristics of lead users play a crucial role in the co-creation process, which varies in different stages of the NDP, separated into the consumer and industrial segments. The proper selection of lead users is essentially important as the quality of contribution highly influences the success of the open innovation process. This could result in a reduced time-to-market ratio and increased profitability.

Based on the results of the SLR and the key arguments, the authors made a contribution to the theory by extending the lead-user method with an additional step of “selection of lead users based on their personal characteristics”. With this extension, we emphasize the relevancy and impact of lead users’ personal characteristics on the entire co-creation process. The importance of the extension is confirmed by the identified 45 primary studies that strongly highlight the positive impact of proper lead users’ personal characteristics on the success of open innovation. We formulated the outcomes of the study in the form of a partial theory named “Lead User Cognition” (LuCog) which is an additional stage in the lead-user method between the steps of “identification of lead users” and “concept design and start of co-creation” phases as Figure 5 shows. The name of the partial theory (LuCog) conveys the essence of the extension as it aims to express the relevance of the lead user cognition process of decision makers during the lead user selection process.

The review also provides a contribution to practice as managers can make a better selection of external contributors (lead users) during their open innovation process. The extended version of the lead-user method provides a crucial tool for decision-makers to select the right lead users for certain stages of the NPD process. The more accurate selection of lead users leads to higher innovation productivity and allows us to reduce development cost and time, shorten the time-to-market factor and help firms to realize a higher profit.

The study has some limitations as the users’ characteristic elements have been investigated only on the individual level. Two characteristic elements, such as “ahead of market trend” and “high expected benefit”, were eliminated from the investigation as the lead-user method contains it in step three (Figure 1). Moreover, we have also omitted the big five personality traits, which were investigated by [74].

Although the Lead-User Theory and Method was created by Eric von Hippel in 1986, the authors decided to review studies published between the time frame of 2000 and 2020 for the following reasons. First, scholars started to reflect on the importance of personal characteristics of lead users only after 2000. Second, the application of the snowballing approach during the study selection process by a manual scan of all references of the primary studies results in relevant studies which may not be covered by the automatic and manual searches.

The snowballing search offered an opportunity to take into consideration the synonyms of the word “characteristics”, e.g., characteristic, attribute, skills, and abilities. We have included all studies that have used any of the synonyms of characteristics and fulfilled the substantial aims of the SLR.

Scholars have generally focused so far on some high-tech industries and consumer products, where lead users are attractive and therefore easy to recognize their activities. Little attention has been paid so far to the role of lead users’ personal characteristics in the hidden domains such as healthcare instruments and tools development or agriculture. Different market contexts require different characteristics which open new perspectives. Further research goals can be derived from the different considerations of our LuCog method. It can be interpreted as the cognition process of managers during their selection process in the fuzzy front end of the co-creation process and also can be understood as a cognition process of lead users by choosing the right firm to co-create. Both topics are neglected in the academic literature.

In sum, further research results in different contexts can lead to a better understanding of the selection criteria of lead users as well as those management techniques which could be applied in open innovation processes. New results facilitate the process wherein managers open their company boundaries in order to tap lead users’ product-related ideas, knowledge, and experience. They can better exploit the advantage of open innovation and adjust open innovation dynamics to changing market conditions and customer needs.