Enhancing Well-Being through Knowledge Sharing: Participants’ Paths

Abstract

This study aimed to explore the mechanism of knowledge sharing as a solution to utilizing individual knowledge that is still untapped, such as user innovation. Prior research has indicated a positive relationship between knowledge sharing and well-being. This study examined participants’ motivation and well-being and compared two types of participants: income-oriented individuals (workers) and hobby-oriented individuals (hobbyists). A questionnaire survey investigated the differences between these two groups in terms of their motivation to engage in knowledge sharing (RQ1) and whether there were disparities in their levels of well-being (RQ2). I found that workers exhibited significantly higher altruism levels as motivation for participating in knowledge sharing, in addition to monetary rewards, compared to hobbyists. Moreover, there was no significant difference in the levels of well-being between the two groups. Overall, this study demonstrates that individuals can improve their well-being by using their knowledge and experience to support others, regardless of whether it is related to income, hobbies, or personal enjoyment.

1. Introduction

With the rise of the sharing economy and the increasing diversity of work styles, there are now more opportunities than ever for individuals to leverage their knowledge and experience. However, the potential of individual knowledge and ideas remains largely untapped. For example, user innovations could increase social welfare, but there is currently no adequate mechanism in society to make use of them [1]. This study fills this gap by highlighting the additional social benefits that can be achieved by utilizing individual knowledge, specifically—that is, improving the well-being of those involved.

This study focuses on knowledge sharing as a mechanism for leveraging individual knowledge. While previous research has examined knowledge sharing between consumers and firms/public sector organizations [2, 3, 4, 5, 6], this study specifically explores consumer-to-consumer (C-to-C) knowledge sharing. Moreover, this study investigates knowledge sharing in both face-to-face interactions and through online platforms. In C-to-C knowledge sharing, not only explicit formal knowledge is exchanged, but also tacit knowledge inherent in individuals is shared through the exchange of experience sharing. In this study, “experience” is defined as tacit knowledge and included in the scope of knowledge sharing.

Innovation by private individuals, referred to as user innovation [7] or household sector innovation [1, 8, 9, 10] in recent studies, is the convergence of personal knowledge. People try to solve some problems using their own knowledge and experience. As users, they possess a deep understanding of the problems at hand and how best to address them [9, 11, 12]. Consistent with previous literature, this study defines innovation as problem-solving.

1.1 Market failure in diffusion of user innovation

User innovation research has long discussed how to elicit innovative ideas that adhere to individuals [7, 13, 14, 15, 16]. This is because most user innovators do not actively disseminate their ideas, since they do not expect incentives appropriate to their effort. Previous studies have indicated that this as a “market failure” [17, 18]. It has been suggested that user innovators create financial value by using their time beyond labor time [19, 20]. It is a great loss for society that even though user innovation could increase social welfare, these are not functioning optimally in real terms.

One effective way to diffuse user innovation is through participation in a community of user innovators [7, 13, 14], and participants’ motivations have been studied. Although financial incentives have been shown to be partially effective [21, 22], the main motivations of community participants have been the fulfillment of personal needs, feedback from others, and enjoyment [21, 22, 23, 24].

Based on the self-determination theory [25, 26, 27], Füller [21] described 10 categories of motivation for those participating in online co-creation projects. The 10 categories are divided into three subcategories: intrinsic, internalized intrinsic, and extrinsic (see details in Table 1). It is revealed that motivation is dependent on the characteristics of the consumer [14].

Motive categories (Füller [21])		Description of this survey
Intrinsic	Intrinsic playful	For fun
	Curiosity	Satisfaction of intellectual curiosity
Internalized extrinsic	Altruism	Own knowledge is useful for someone else
	Make friends	Interaction with others who share common interests
	Self-efficacy	Opportunity to test own knowledge and skill
	Information seeking	Obtaining useful information
	Skill development	Improvement of one’s skills
	Recognition	Visualization of evaluations from others
Extrinsic	Needed	Requested, unique to me, and so on
	Reward	Income generation

Table 1.

Motivation items.

1.2 Knowledge sharing as a solution for diffusion of user innovation

Belk [28] has defined sharing as “the act and process of distributing what is ours to others for their use and/or the act and process of receiving or taking something from others for our use” and has demonstrated its effectiveness [29, 30]. Previously, it was noted that knowledge sharing has contributed to the development of education, culture, computing, and so on [31, 32]. With the development of the sharing economy, various platforms have been established, making it easier for individuals to disseminate and monetize their ideas. The same is true for user innovation, which can be regarded as the accumulation of individual knowledge.

Aoki [33] found that knowledge sharing is a solution to the market’s failure in diffusing user innovation. It seems that through knowledge sharing, participants may be able to satisfy all the motivations Füller [21] indicated, including extrinsic motivation of reward, as well as intrinsic motivation, such as enjoyment, and internalized extrinsic motivation, such as interacting with others and gaining recognition. This study empirically confirms this through a survey of knowledge-sharing participants.

1.3 Relationship between knowledge sharing and well-being

Aoki [33] numerically demonstrated that knowledge-sharing participants do not only receive rewards but also improve their well-being, using the concept of “flourishing” in positive psychology [34]. Well-being has been distinguished from happiness in that it does not only deal with satisfaction with life or positive feelings, but it is also comprehensive in terms of relationships with others, autonomy, and achievement [34, 35, 36, 37]. The process of knowledge acquisition and utilization by individuals is a continuous process and could be highly congruent with the concept of well-being. Aoki [33] visualized the nonmonetary incentives gained by knowledge-sharing participants with various motivations, in terms of improved well-being.

Flourishing is a criterion for measuring well-being and consists of the following five elements: positive emotion, engagement, relationships, meaning, and accomplishment (PERMA) [34]. Positive emotion is the degree of happiness and enjoyment [34] and is relative to enjoyment, which has been considered an important motivation for user innovators [21, 22, 23, 24]. Engagement is the degree of absorption in something [34], or “flow,” as proposed by Csikszentmihalyi [38] and Nakamura and Csikszentmihalyi [39]. When people acquire new knowledge or try to create something with it, they may be absorbed in the act. Relationships refer to positive relationships with others [34]. Interaction with others has been identified as an important motivation for people to participate in innovation communities [21, 22, 23, 24]. Furthermore, participation in knowledge sharing inevitably leads to interaction with others. Meaning is the degree of satisfaction with one’s life, and accomplishment is the degree of achievement of goals set by oneself. If their knowledge and ideas are utilized or recognized by someone else, people may find meaning in it and feel a sense of accomplishment. Thus, knowledge sharing in the form of diffusion of user innovation and PERMA are considered to have a deep relationship.

Although it is generally difficult to measure nonmonetary incentives, Butler and Kern [40] developed a PERMA measurement consisting of 15 questions (3 for each element of PERMA) in which respondents provide ratings on an 11-point scale from 0 to 10 (for details, see Appendix Table A1). Aoki [33] showed that knowledge-sharing participants were significantly higher than nonparticipants in four of the five PERMA elements.

Why, then, do knowledge-sharing participants have higher levels of well-being? Aoki [41] investigated this question through in-depth interviews with 10 knowledge-sharing participants who were transferring their knowledge and experience through activities using Lego bricks. She concluded that participants’ well-being was enhanced through the following process:

1. Sharing knowledge.

2. Deepening the knowledge and experience they have cultivated over the years.

3. Finding meaning in passing on this knowledge and experience to the next generation.

1.4 Knowledge-sharing positioning and research question

Knowledge-sharing participants include those who do so through work and as an extension of hobbies. This study examines whether there is a difference in the paths that the participants followed in either case. Prior research has indicated that monetary incentives and social reputation are conflicting sources of motivation for sharing [31]. Benkler [31] introduced a study comparing paid and free blood donation programs, and the result was that the free blood donation campaign received more cooperation from the public [42]. In the field of psychology, extrinsic and intrinsic motivations have been discussed as contradictory concepts since Deci [43], who stated that monetary incentives could delegitimize intrinsic motivation. Behavioral economics research has pointed out that when monetary incentives are introduced into a market where social incentives function, the former ceases to function [44, 45].

Aoki’s [41] study included a mixture of those who were involved in Lego as a hobby and those who became involved in Lego as a job after their hobby developed into a career. She found no differences between the two groups in the process of improving their well-being, such as satisfying their own intellectual curiosity and a sense of mission to pass on to the next generation. It is necessary to confirm whether this result is due to Lego or whether generalization is possible. This study examines the differences between the two groups: “workers,” who are income-oriented participants, and “hobbyists,” who are motivated by something other than monetary rewards such as a hobby, in terms of motivation and well-being (Figure 1). This study focuses on addressing the following research questions.

Figure 1.

Research framework.

RQ1: What are the differences in terms of motivation to participate in knowledge sharing between “workers” and “hobbyists”?

RQ2: Are there any differences in the level of well-being between “workers” and “hobbyists” in knowledge sharing?

1.5 Hypotheses

With respect to “workers,” who function for income purposes, the following hypothesis is derived for RQ1.

H1: In knowledge sharing, while “workers” are more extrinsically motivated, “hobbyists” are more intrinsically motivated.

As noted earlier, intrinsic and extrinsic motivation have been shown to conflict in psychology and behavioral economics [31, 42, 43, 44, 45]. However, it is necessary to carefully examine whether any difference exists in the resulting improvement in well-being obtained by those who participate in knowledge sharing with their individual motivations. Studies on the relationship between wealth and happiness have commonly shown that the more wealth one has, the higher the level of life satisfaction, but at a certain level, a point of diminishing returns is reached [34]. The knowledge sharing addressed in this study is focused on what takes place during nonlabor time, and that income, if any, is an additional entity; therefore, the impact on well-being is likely to be limited. This leads to the following hypothesis for RQ2.

H2: There are no significant differences in the level of well-being between “workers” and “hobbyists.”

2. Materials and methods

1. To answer the research questions, a questionnaire survey was conducted with knowledge-sharing participants using the following procedures: Comparative analysis of knowledge participants and a control group (nonparticipants).

2. Comparative analysis of “workers” who participate for remuneration purposes and other knowledge-sharing participants, the “hobbyists.”

2.1 Sample

The sample of knowledge sharing participants was collected through a research agency via the proceeding steps. First, with the goal of securing a total of 1,000 participants, the following screening questions were asked to 50,000 participants between the ages of 18 and 65 years (age, sex, and residential area in this age group were in line with the population ratio of Japan).

1. Do you have experience in knowledge sharing within the last 12 months? Knowledge sharing refers to using your knowledge, experience, and skills to earn remuneration, primarily money, whenever you want, such as during your spare time. This includes even selling handmade works and so on using your knowledge and skills.

2. Please select the closest match to your knowledge-sharing position.

1. Secondary occupation or necessary source of income

2. As a hobby or for fun

3. Volunteer work

4. Other

Those who answered “yes” to the first question proceeded to the second question; those who chose a) for the second question were classified as “workers” and those who chose otherwise as “hobbyists.”

Simultaneously, a control group of 1,000 men and women aged 18 to 65 years (age, sex, and residential area in this age group were in line with the population ratio in Japan) was selected.

2.2 Variables and measurement

2.2.1 Motivation to participate in knowledge sharing

To examine the difference in terms of motivation between “workers” and “hobbyists” (RQ1), the data was collected using the motivation items presented by Füller [21]. Füller [21] extracted these categories covering intrinsic and extrinsic motivation from diverse literature, including psychology, research on open-source software communities, word-of-mouth, and so on. Although participant motivations or incentives have been presented in knowledge-sharing studies [4, 5, 6], primarily extrinsic motivations or incentives have been discussed. This study refers to Füller [21] in order to focus on intrinsic motivation in addition to extrinsic motivation.

The motivation items were presented to the respondents in a manner consistent with those of knowledge sharing, as follows (Table 1). Respondents evaluated each item using a 7-point Likert scale.

2.2.2 PERMA

To examine the difference in terms of well-being between “workers” and “hobbyists,” (RQ2) the level of well-being was based on the concept of flourishing comprising the five PERMA elements, as presented by Seligman [34].

Prior research has suggested that measures of well-being should be multidimensional [35, 36, 37] and universal in their global applicability [37]. The scale of Butler and Kern [40] has been validated through 11 quantitative surveys covering the Americas, Europe, Asia, Africa, and Oceania; Aoki [33] used a Japanese translation of the scale in her study after a back-translation process. In this study, a Japanese translation of the questions was used in the same manner.

Respondents evaluated each item from 0 to 10 (see details in Appendix Table A1). As recommended, the level of PERMA should be measured by the average of three responses for each element [40], and this was followed here.

2.2.3 Control variables

As control variables, this study collected data on age; sex (male: 1, female: 0); marital status (married: 1, never married: 0); employment status (1: unemployed, 2: part-time, 3: full-time); educational background (1: junior high school, 2: high school, 3: junior college, 4: university, 5: graduate school, and 7: high school); ordinal measure of the length of education (1: junior college/university, 3: university); and personal annual income (ordinal scale; 1: 0 yen, 2: less than 1 million yen, 3: less than 2 million yen, 11: less than 10 million yen, 12: less than 12 million yen, 13: less than 15 million yen, 14: less than 20 million yen, 15: more than 20 million yen).

2.3 Analysis

To test H1, a mean comparison is made between workers and hobbyists for each of the 10 motivation items. If the results show that workers exhibit higher levels of extrinsic motivation while hobbyists demonstrate higher levels of intrinsic motivation, H1 would be supported.

To test H2, a mean comparison is made between workers and hobbyists for each PERMA element. Prior to this analysis, a comparison of means is performed between knowledge-sharing participants and nonparticipants for each PERMA element. This step is necessary to ensure that knowledge-sharing participants have higher levels of well-being [33]. If a significant difference is found, a multiple regression analysis is conducted. The group dummy variable (participation to knowledge sharing; yes: 1, no: 0) is included as an independent variable along with control variables, and each PERMA element is treated as a dependent variable. This analysis aims to determine if the significant difference persists even after excluding the effects of control variables. If the results indicate no significant difference in any of the PERMA elements between workers and hobbyists, H2 would be supported.

3. Results

3.1 Sample

As a result of screening, data were obtained for 1,025 knowledge-sharing participants and 1,042 in the control group. Since the latter group included 59 knowledge-sharing participants, the analyses included them in the former group. After carefully reviewing the responses and omitting those that were unreliable or did not meet the definition of knowledge sharing for the purpose of this study, data from 1,031 knowledge-sharing participants (M_age = 41.8 years, 58.9% male participants) and 983 nonparticipants (M_age = 43.9 years, 49.5% male participants) was finally used for the analysis. Table 2 breaks down the positioning of knowledge sharing among the participants (n = 1031) as a result of the screening questions. Those who chose a) in Table 2 were classified as “workers” (n = 419), and those who chose otherwise as “hobbyists” (n = 612).

	n	%
a. Secondary occupation or necessary source of income	419	40.6%
b. As a hobby or for fun	495	48.0%
c. Volunteer work	110	10.7%
d. Other	7	0.7%
Total	1031	100.0%

Table 2.

Positioning of knowledge sharing.

The participants’ knowledge ranged from creative works to languages and child-related, etc. (Table 3).

	n	%
Creative works; videos, photos, handmade works, etc.	307	29.8%
Lifestyle; housework, cleaning, cooking, etc.	250	24.2%
Information technology	226	21.9%
Languages	187	18.1%
Design	168	16.3%
Child-related: childcare, education, etc.	158	15.3%
Others	133	12.9%

Table 3.

Participants’ knowledge-sharing categories.

Note. Multiple answers.

3.2 Comparison of knowledge-sharing participants and nonparticipants

First, I compare the PERMA levels of knowledge-sharing participants and nonparticipants: for the PERMA scale, it includes a Cronbach’s alpha slightly below 0.8, which is an acceptable level consistent with previous research; and the 15 items of Butler and Kern’s scale [40] were used in the analysis. The results showed that knowledge-sharing participants were significantly higher at the 0.1% level in all five PERMA elements (Table 4).

	α	Knowledge-sharing participants (n = 1031)		Nonparticipants (n = 983)		t-value
		M	SD	M	SD
PERMA
Positive emotion	0.85	6.23	1.77	5.57	1.75	8.45	***
Engagement	0.85	6.46	1.62	5.63	1.61	11.57	***
Relationship	0.79	6.04	1.82	5.66	1.87	4.68	***
Meaning	0.82	6.03	1.83	5.18	1.91	10.16	***
Accomplishment	0.89	6.34	1.68	5.52	1.67	11.00	***

Table 4.

PERMA of the respondents.

***p < .001.

Next, to verify the validity, multiple regression analysis was conducted with the knowledge-sharing participation (yes: 1, no: 0) and the control variable as independent variables and each element of PERMA as a dependent variable. Prior to the analysis, the normality of the residuals for each variable was verified. Missing values were also excluded for each pair. To avoid multicollinearity, “employment status” with a variance inflation factor (VIF) greater than 10 was excluded from the independent variables. The results of the analysis show that participation in knowledge sharing significantly affects each of the PERMA components at the 0.1% level, even after excluding the effects of control variables, for all PERMA components, including Relationship, which did not reach significance in Aoki’s [33] study (Table 5).

Dependent variable	Positive emotion		Engagement		Relationship		Meaning		Accomplishment		VIF
	β		β		β		β		β
Independent variable
Knowledge sharing	0.12	***	0.14	***	0.09	***	0.14	***	0.13	***	2.04
Sex	−0.01		0.02		−0.02		0.00		0.02		3.01
Age	0.40	***	0.41	***	0.36	***	0.31	***	0.39	***	7.56
Marital status	0.02	*	−0.03	*	0.03		0.04	*	−0.01		2.56
Educational background	0.46	***	0.49	***	0.53	***	0.47	***	0.46	***	7.69
Personal income	0.01		−0.03		−0.01		0.05	*	0.01		5.43
R^2	0.89		0.90		0.88		0.88		0.91
F	2213.44	***	2463.70	***	1909.52		1916.45	***	2543.65	***

Table 5.

Results of regression analysis (PERMA and knowledge sharing).

** p < 0.01; ***p < 0.001.

3.3 Comparison of workers and hobbyists in PERMA (H2)

To examine H2, I compared the two groups on the level of PERMA, and there were no significant differences between workers and hobbyists for all elements (Table 6). Therefore, H2 is supported.

	α	Workers (n = 419)		Hobbyists (n = 612)		t-value
		M	SD	M	SD
PERMA
Positive emotion	0.85	6.27	1.84	6.20	1.72	0.61
Engagement	0.79	6.47	1.69	6.45	1.58	0.14
Relationship	0.81	6.02	1.96	6.05	1.72	0.26
Meaning	0.87	6.04	1.98	6.03	1.71	0.06
Accomplishment	0.84	6.42	1.73	6.28	1.63	1.29

Table 6.

PERMA of the knowledge-sharing participants.

3.4 Comparison of workers and hobbyists in motivations (H1)

To examine H1, I compared the motivations for participating in knowledge sharing between two groups and found that “altruism” (p < 0.05) and “reward” (p < 0.001) were significantly higher for the workers than for the hobbyists (Table 7). While the result for “reward” is in line with the hypothesis, the result for “altruism” is contrary to the hypothesis. Therefore, H1 is not supported. The important implications of this result are discussed in detail in the discussion section.

	Workers (n = 419)		Hobbyists (n = 612)		t-value
	M	SD	M	SD
Intrinsic playful	4.96	1.50	4.87	1.53	0.95
Curiosity	4.78	1.47	4.66	1.43	1.31
Altruism	5.04	1.50	4.83	1.42	2.16	*
Make friends	4.57	1.50	4.51	1.46	0.59
Self-efficacy	4.87	1.44	4.75	1.40	1.32
Information seeking	4.63	1.45	4.54	1.45	1.05
Skill development	4.98	1.46	4.82	1.46	1.72
Recognition	4.63	1.42	4.48	1.37	1.70
Needed	4.75	1.50	4.64	1.41	1.15
Reward	5.08	1.57	4.27	1.55	8.19	***

Table 7.

Motivations of the knowledge-sharing participants.

* p < .05; ***p < .001.

3.5 Motivations influencing well-being

The findings indicate that the level of well-being of knowledge-sharing participants is significantly higher than that of nonparticipants, and there is no significant difference in the level of well-being whether knowledge sharing is positioned as a secondary job or hobby, volunteer activity, and so on. In addition, there are no other significant differences in the motivation to participate in knowledge sharing between workers and hobbyists, except for rewards and altruism.

Which motivations for participation in knowledge sharing will influence the level of well-being? Ultimately, multiple regression analysis was conducted with each element of PERMA as the dependent variable and motivation to participate in knowledge sharing and the control variables as independent variables. The results showed that altruism significantly influenced all the PERMA elements; intrinsic playful significantly influenced the four elements except accomplishment; Information seeking significantly influenced positive emotion and accomplishment; and curiosity significantly influenced engagement (Table 8). The motivational items demonstrated by Füller [21] are ordered from intrinsic to extrinsic. The four items that were significant in this analysis are concentrated in the first half of the motivational items. These results suggest that intrinsic motivations influence well-being.

Dependent variable	Positive emotion		Engagement		Relationship		Meaning		Accomplishment		VIF
	β		β		β		β		β
Independent variable
Motivations
Intrinsic playful	0.12	*	0.10	*	0.12	*	0.11	*	0.02		2.53
Curiosity	0.05		0.10	*	0.03		0.08		0.07		2.49
Altruism	0.12	*	0.16	***	0.10	*	0.16	***	0.21	***	2.53
Make friends	0.08		0.00		0.08		0.04		0.02		1.79
Self-efficacy	0.07		0.08		0.07		0.08		0.08		2.74
Information seeking	0.09	*	0.06		0.06		0.07		0.08	*	1.98
Skill development	−0.02		0.01		−0.02		−0.02		0.00		2.91
Recognition	−0.03		0.04		−0.04		0.00		0.02		2.08
Needed	0.02		0.02		−0.03		−0.06		0.07		2.45
Reward	0.00		0.02		−0.03		−0.06		0.04		1.35
Control variables
Sex	−0.01		0.00		−0.01		0.03		−0.01		1.39
Age	−0.08	*	−0.09	**	−0.15	***	−0.14	***	−0.08	*	1.34
Marital Status	0.09	*	0.00		0.13	***	0.12	***	0.03		1.27
Educational background	0.04		0.04		0.08	*	0.07	*	0.09	**	1.15
Employment status	−0.04		−0.07		−0.05		−0.06		−0.03		1.63
Personal income	0.09	*	0.05		0.05		0.14	***	0.10	*	2.00
R^2	0.17		0.23		0.10		0.15		0.24
F	11.51	***	16.44	***	7.16	***	10.13	***	17.88	***

Table 8.

Results of regression analysis (PERMA and motivations).

* p < .05; ***p < .001.

4. Discussion

4.1 Findings

This study aimed to explore the utilization of untapped individual knowledge, such as user innovation, by investigating the mechanism of knowledge sharing as a solution. Specifically, the study examined the differences in motivation and well-being between two groups: “workers” and “hobbyists.” The study yielded significant findings, which are summarized as follows:

Contrary to hypothesis H1, the “altruism” motivation was significantly higher in the worker group (whose main objective should be rewards), than in the hobbyist group, including those who engage in knowledge sharing as volunteer work. This finding suggests that factors such as a stronger sense of responsibility or mission, or a recognition of the value of one’s own knowledge and experience as a result of the rewards. Notably, rewards serve as an objective evaluation of the value of personal knowledge, in addition to their monetary value.

Hypothesis H2 was supported, as no significant differences were found in any of the PERMA elements related to the level of well-being between workers and hobbyists. This study extends the findings of Aoki [33], indicating that participation in knowledge sharing enhances the well-being of participants across all five PERMA elements, even when the primary motivation is monetary compensation.

Furthermore, an additional analysis of the relationship between participants’ motivation and PERMA revealed that knowledge-sharing participants enhance their well-being by contributing to others while simultaneously acquiring valuable information and satisfying their intellectual curiosity, in addition to personal enjoyment. This result aligns with and quantitatively verifies Aoki’s [41] finding that knowledge-sharing participants experience increased well-being when they find meaning in deepening their own knowledge and passing it on to others, including future generations.

In summary, this study demonstrates that individuals can enhance their well-being by utilizing their knowledge and experience to support others, regardless of whether it is for income, hobbies, or enjoyment.

4.2 Implications

This study makes several contributions to the existing research on user innovation. First, while user innovation has been recognized as a means to enhance overall social welfare [19, 20], the lack of appropriate incentives has hindered its widespread implementation [17, 18]. Although public support has been suggested as a solution [1], this study highlights the effectiveness of C-to-C knowledge sharing as an alternative solution. Individual ideas often possess niche appeal to specific target audiences, and in the initial stages, C-to-C knowledge sharing, which directly matches supply and demand, can prove more effective. Therefore, this study not only demonstrates a pathway for the application of user innovation to enhance social welfare but also identifies the nonmonetary value perceived by user-innovators. While prior research has suggested enjoyment, learning, and interaction with others as important motivations [21, 22, 23, 24], this study provides quantitative evidence using the PERMA scale.

Note that the additional analysis in this study identifies a significant relationship between certain motivational factors and the elements of PERMA, but it does not reveal the pathway. Further research is needed.

In the context of knowledge sharing research, this study diverges from previous studies that have primarily focused on knowledge sharing between firms and consumers, instead emphasizing C-to-C knowledge sharing. While prior research has highlighted extrinsic motivation and incentives as driving factors [4, 5, 6], this study suggests intrinsic motivation among participants. However, further investigation is required to determine if the effects observed in C-to-C knowledge sharing can be applied to knowledge sharing between firms and consumers.

The COVID-19 pandemic has significantly impacted people’s well-being [46, 47, 48] and altered their work patterns. From a practical perspective, this study suggests that knowledge sharing can serve as a secondary job, allowing individuals to contribute to others while earning income. With the rise of remote work and the gig economy, many employees face restrictions on engaging in secondary business activities. Concerns about interference with company operations, intellectual property leakage, and trust issues exist. However, considering the improvement of employee well-being, it is crucial for companies to be open to leveraging their employees’ individual knowledge.

The pandemic has also damaged the sharing economy [49, 50], which has been growing at an accelerated pace. Movement restrictions, logistics challenges, and the need for social distancing have contributed to this decline. Knowledge sharing, by contrast, has been minimally affected by these factors, with increased interest observed in freelance work during lockdown periods [50].

Finally, the study discusses the results from a sustainability perspective. It emphasizes that acquiring knowledge alone does not bring fulfillment; rather, the true value lies in the application and utilization of knowledge. Using knowledge for the benefit of others, whether through paid or unpaid means, not only deepens one’s own knowledge but also enhances well-being. This study established a sustainable flow of knowledge acquisition and utilization within individuals, applicable at any stage in life, including work, leaves of absence, and retirement. The accumulated knowledge within individuals is truly diverse. The study concludes with the hope that it will facilitate the transfer of individuals’ knowledge to society, fostering greater diversity in sustainable knowledge resources.

Acknowledgments

This work was supported by JSPS Grants-in-Aid for Scientific Research (Grant Number 20 K13631, 22 K01759).

Appendix

Label	Question	Response Anchors
A1	How many times do you feel you are making progress toward accomplishing your goals?	0 = never, 10 = always
E1	How often do you become absorbed in what you are doing?
P1	In general, how often do you feel joyful?
N1	In general, how often do you feel anxious?
A2	How often do you achieve the important goals you have set for yourself?
H1	In general, how is your health?	0 = terrible, 10 = excellent
M1	In general, to what extent do you lead a purposeful and meaningful life?	0 = not at all, 10 = completely
R1	To what extent do you receive help and support from others when you need it?
M2	In general, to what extent do you feel that what you do in your life is valuable and worthwhile?
E2	In general, to what extent do you feel excited and interested in things?
Lon	How lonely do you feel in your daily life?
H2	How satisfied are you with your current physical health?	0 = not at all, 10 = completely
P2	In general, how often do you feel positive?	0 = never, 10 = always
N2	In general, how often do you feel angry?
A3	How often are you able to handle your responsibilities?
N3	In general, how often do you feel sad?
E3	How often do you lose track of time while doing something you enjoy?
H3	Compared to others of your same age and sex, how is your health?	0 = terrible, 10 = excellent
R2	To what extent do you feel loved?	0 = not at all, 10 = completely
M3	To what extent do you generally feel you have a sense of direction in your life?
R3	How satisfied are you with your personal relationships?
P3	In general, to what extent do you feel contented?
Hap	Taking all things together, how happy would you say you are?	0 = not at all, 10 = completely

Table A1.

23-item PERMA profiler measure [40].

Note. Of the 23 questions in this study, 15 were used in the analysis.

Nomenclature

Innovation	value creation for problem-solving
User innovation	innovation by users involving general individuals
Knowledge sharing	providing knowledge and experience from those who own it to those who need it
Well-being	being in good health both mentally and physically