Introduction
Digital technologies, such as telephone penetration, internet, and broadband penetration (Dzator, Acheampong, Appiah-Otoo, & Dzator, Reference Dzator, Acheampong, Appiah-Otoo and Dzator2023) are often seen as the means to end poverty (Duvendack, Sonne, & Garikipati, Reference Duvendack, Sonne and Garikipati2023; Inoue, Reference Inoue2024), and ‘empower people by enabling them to access, use, and share information’ (Lechman & Popowska, Reference Lechman and Popowska2022: 1). Such information enables users to acquire knowledge that can be used to reduce poverty. As another example, information and communication technologies developed during the pandemic enabled poverty reduction by providing access to better healthcare and allowing users to remain socially connected. Duvendack et al. (Reference Duvendack, Sonne and Garikipati2023) discuss the efforts of the Indian government to drive digital financial inclusion to reduce poverty among poor rural women. Such digital financial inclusion provides the means for women to gain access to digital financial services that can provide access to finances and a platform for these women to exploit opportunities. Digital technologies are thus seen as powerful means to reduce poverty.
Given the importance of digital technologies and the critical need to reduce poverty through innovation and entrepreneurship (Bruton, Ahlstrom, & Si, Reference Bruton, Ahlstrom and Si2015; Si, Ahlstrom, Wei, & Cullen, Reference Si, Ahlstrom, Wei and Cullen2020; Wu, Si, & Wu, Reference Wu, Si and Wu2016), in this article, we examine the social innovation efforts to provide online platforms, a form of digital technology, to enable smallholder Japanese farmers to sell their products to escape poverty. Social innovation refers to innovation that addresses a social problem through a process that is also social, involving a range of external stakeholders in society (Ashta, Couchoro, & Musa, Reference Ashta, Couchoro and Musa2014; Pfitzer, Bockstette, & Stamp, Reference Pfitzer, Bockstette and Stamp2013; Prahalad, Reference Prahalad2012; Silva-Flores & Ladron de Guevara-jimenez, Reference Silva-Flores and Ladron de Guevara-jimenez2019; Voorberg, Bekkers, & Tummers, Reference Voorberg, Bekkers and Tummers2015). By mobilizing stakeholders extensively to address economic, social, and environmental issues for human well-being, social innovation is also considered a specific framework for promoting sustainable development and reducing poverty (Da Costa, Larentis, & De Carvalho, Reference Da Costa, Larentis and De Carvalho2022).
Given the above, the article addresses several gaps. First, while research overwhelmingly supports the link between digital technologies and poverty reduction, most studies have been examined at a macro level. For instance, studies by Dzator et al. (Reference Dzator, Acheampong, Appiah-Otoo and Dzator2023), Bergantino, Intini, and Nademi (Reference Bergantino, Intini and Nademi2025), and Dong, Cui, Bai, and Liu (Reference Dong, Cui, Bai and Liu2024) all rely on macro-level indicators such as broadband penetration by a city or composite IT penetration on city or country poverty levels (Lechman & Popowska, Reference Lechman and Popowska2022). To our knowledge, we could not find micro-level studies that examine the mechanisms of such links. Using a combined qualitative and secondary data approach, we reveal a more fine-grained understanding of the link at an individual level, thereby providing a more refined understanding of the mechanisms linking digital technologies and poverty reduction.
A second gap we address is the lack of research explaining why some digital technologies work while others do not. For example, Bergantino and colleagues (Reference Bergantino, Intini and Nademi2025) used panel data from 28 European nations to show that access to Information Communications Technologies significantly impacted poverty reduction. However, while such studies have shown the value of digital technologies, Dzator et al. (Reference Dzator, Acheampong, Appiah-Otoo and Dzator2023) find that digital technologies may sometimes increase poverty rates. Our stakeholder mobilization approach enables us to understand why the use of digital technologies for addressing the poverty issue of smallholder farmers in Japan succeeded in some cases, but not in others. Such findings provide useful guidance on enhancing the effects of digital technologies.
A third gap we try to address is the lack of understanding of the process behind social innovation. Many studies have explored social innovation using a dual perspective of outcome vs. process view, like many phenomena that are the subjects of scientific inquiries. While the outcome side of social innovation has received relatively extensive research (e.g., Chan, Chui, Chan, & Yip, Reference Chan, Chui, Chan and Yip2019; Von Jacobi, Chiappero-Martinetti, Maestripieri, & Giroletti, Reference Von Jacobi, Chiappero-Martinetti, Maestripieri and Giroletti2024; Xiao, Roh, Ghauri, Cho, & Park, Reference Xiao, Roh, Ghauri, Cho and Park2024), studies on the process of social innovation are so far somewhat limited in the literature (Lashitew, Bals, & Van Tulder, Reference Lashitew, Bals and Van Tulder2020; Mulgan, Reference Mulgan2006). Few studies exist that attempt to capture how stakeholders get mobilized and drive the process of social innovation despite the importance of stakeholder mobilization in the literature (Pfitzer et al., Reference Pfitzer, Bockstette and Stamp2013; Prahalad, Reference Prahalad2012; Silva-Flores & Ladron de Guevara-jimenez, Reference Silva-Flores and Ladron de Guevara-jimenez2019). This gap in the literature is not surprising given the difficulty of studying the processes using the more traditional quantitative approaches.
In response to these gaps, we conducted a qualitative study on the process of social innovation in terms of stakeholder mobilization that propels the process, following the framework of case-based research (Yin, Reference Yin2014). Over a million smallholder farmers in Japan face increasingly unsustainable challenges such as severe low income, retirement ages, and the unavailability of successors (Agri-Navi, n.d.). The problem is so severe that it recently led to rice farmers’ protests in Tokyo (Economist, 2025). To address these challenges, we study six social enterprises that developed online platforms to enable these farmers to sell directly to consumers, thereby resulting in poverty reduction through higher incomes and other non-monetary rewards through direct interactions with end consumers. As such, consistent with the special issue theme, we attempt to explain the process by which digital technologies in the form of an online platform have helped Japanese smallholder farmers increase their income and escape poverty. Furthermore, using these technologies also enabled these farmers to become more comfortable with technology, thereby addressing digital poverty reduction. Therefore, we address several questions posed by the special issue (specifically, how do entrepreneurs and governments reduce social poverty through digital technology or network models in different regions and countries and what are the roles of digital networks and digital platforms by individuals living in severe poverty as they seek to either found or grow a business?) by examining how these Japanese smallholder farmers can use digital platforms to grow their business.
Given the above, we offer several contributions to the literature. First, we elucidate the black box of stakeholder mobilization and provide a better theoretical understanding of the process. Although various theories can be used to explain the link between digital technologies and poverty reduction (e.g., modernization theory [Inglehart & Baker, Reference Inglehart and Baker2000], whereby changes in societies lead to transformation or network effects theory [Borgatti & Halgin, Reference Borgatti and Halgin2011], whereby as more people can access digital technologies, benefits multiply), we derive a schematic model based on Slaughter’s (Reference Slaughter2017) framework on how stakeholders get mobilized and drive the social innovation process, thereby reducing poverty. Slaughter’s (Reference Slaughter2017) approach is more appropriate for our examination as her central thesis is that entities must engage in several networking activities to benefit from an increasingly interconnected world. The model captures the social innovation process in terms of essential stakeholder tasks advancing the process individually and collectively through their nonlinear dependencies. In demonstrating the explanatory power of the proposed model, we then offer a systematic account of why and how the two successful platforms, among the six cases we have studied, have done well with poverty reduction, while four others have failed and terminated their operations. We conclude with the implications for future research.
Literature Review
Digital Technologies, Poverty Reduction, and Social Innovation
As mentioned earlier, the research on the impact of digital technologies overwhelmingly supports poverty reduction (Bergantino, Intini, & Nademi, Reference Bergantino, Intini and Nademi2025). Access to basic digital technologies such as mobile phones is seen as freedom-enhancing, which can improve social inclusion and progress (Sen, Reference Sen2010). Furthermore, using digital technologies to improve the financial inclusion of traditionally ignored groups can also have beneficial effects (Dong et al., Reference Dong, Cui, Bai and Liu2024; Inoue, Reference Inoue2024) as it allows such groups to access financial services such as loans, payments, and insurance services, thereby enhancing the success of entrepreneurial ventures. Lechman and Popowska (Reference Lechman and Popowska2022) further argue that access to digital technologies also empowers people by allowing them to access and share information. Such access is also likely linked to people getting more educated about the critical skills needed to escape poverty. Given the overwhelming evidence of such links, Dzator et al. (Reference Dzator, Acheampong, Appiah-Otoo and Dzator2023: 2) conclude that digital technologies ‘contributes to poverty reduction by facilitating economic growth, financial inclusion, employment generation, health, education, democracy, and inclusive governance’.
To address the theme of the special issue, we use a qualitative approach to demonstrate how the adoption of digital technologies contributed to social innovation and thereby enabled Japanese farmers to escape poverty. Following Terwiesch and Ulrich (Reference Terwiesch and Ulrich2009), we adopt the definition of ‘innovation’ as a new match between a problem and a solution. In other words, if there is an old problem and an old solution, and their match is new, it is an innovation. Our definition of social innovation, therefore, is an innovation that addresses a social problem by involving relevant stakeholders in society. For example, the microfinance solution, originally developed in Bangladesh, addressed the poverty issue in Bolivia (Battilana & Dorado, Reference Battilana and Dorado2010). However, the socio-cultural context of Bolivia was different from that of Bangladesh; therefore, the microfinance scheme had to be adapted to the new context of Bolivia and its culture to address the poverty issue (Battilana & Dorado, Reference Battilana and Dorado2010). In this way, the microfinance solution and Bolivia’s poverty issue were a new match, and therefore, a case of social innovation using our definition. The same can be said for the poverty issue of smallholder farmers in Japan and the online platform solution. The poverty issue is not a new issue, and neither is the online platform a new and innovative solution. However, the match between the two is a new match, making it a case of social innovation.
We therefore investigate how stakeholders can be mobilized to engage in an activity that constitutes a form of social innovation for poverty reduction. We review key process insights gained by these prior studies while focusing on the process of how such various outcomes may derive in social innovation. We then summarize the research gap that this article addresses.
Stakeholder Mobilization
A literature review underscores the significance of stakeholder mobilization when undertaking the process of social innovation. The most notable is the large-scale involvement of stakeholders in the process, often across two or more sectors (Chan et al., Reference Chan, Chui, Chan and Yip2019; Pfitzer et al., Reference Pfitzer, Bockstette and Stamp2013; Prahalad, Reference Prahalad2012; Silva-Flores & Ladron de Guevara-jimenez, Reference Silva-Flores and Ladron de Guevara-jimenez2019). This is consistent with the general understanding that social innovation addresses socially widespread issues and necessitates a correspondingly extensive mobilization of various stakeholders. For instance, in addressing the challenge of health hazards among the poor in India caused by pollutant-producing biomass stoves, the key solution was the innovation of smoke-free biomass stoves and specific biomass pellets (Prahalad, Reference Prahalad2012). However, since the poor in India were spread throughout the country, the solution deployment required a large-scale involvement of multiple stakeholders, particularly an extensive, village-level entrepreneurial network of local women for stocking and distributing newly invented stoves and biomass pellets (Prahalad, Reference Prahalad2012). It is worth noting here that inclusive stakeholder participation is also beneficial to a comprehensive understanding (not just a far-reaching solution) of the social problem due to its multi-dimensional complexity (e.g., social, economic, political, and environmental dimensions) (Pfitzer, Bockstette, & Stamp, Reference Pfitzer, Bockstette and Stamp2013).
Business-driven social innovation offers a potentially fertile opportunity to study how stakeholders get mobilized and engage in ‘joint value creation’, a research theme that has been receiving considerable attention in the recent development of stakeholder theory (Freudenreich, Lüdeke-Freund, & Schaltegger, Reference Freudenreich, Lüdeke-Freund and Schaltegger2020; Tapaninaho & Heikkinen, Reference Tapaninaho and Heikkinen2022). Following the insight of Slaughter (Reference Slaughter2017) in a larger context of social network formation, we consider, in this study, five essential ‘tasks’ on how stakeholders get mobilized to engage in joint value creation, namely (1) ‘clarification’ in which a ‘joint purpose’ is articulated and shared among stakeholders; (2) ‘curation’ through which stakeholders join a platform for joint value creation; (3) ‘connection’ through which stakeholders obtain a means of interaction for joint value creation; (4) ‘cultivation’ in which stakeholders nurture mutual trust and prepare for joint value creation; and (5) ‘catalyzation’ in which stakeholders engage in value creation activities that are aligned with the joint purpose set in ‘clarification’. Throughout, we refer to this framework as ‘five Cs’.
Methods
This study follows the framework of case-based empirical research (Yin, Reference Yin2014), to build conceptual insights on the process of social innovation in terms of stakeholder mobilization. Additionally, we follow Köhler’s (Reference Köhler2016) transparency guidelines and provide adequate information so the reader can understand how the research unfolded. Below, we discuss the setting and the process we followed in answering our earlier research questions.
Research Setting
The research setting of this study is a form of digital technology, specifically buy-and-sell online platforms of fresh produce that provide direct-to-consumer distribution channels for smallholder farmers facing multiple challenges in Japan. According to the Minister of Agriculture, Forestry and Fishery (MAFF), there were around 1,037,000 smallholder farmers in 2020 (MAFF, 2021). Their average annual income was 1,900,000 yen in 2019 (MAFF [Ministry of Agriculture, Forestry and Fishery], 2020), roughly 13,000 USD (as of 2023), which was about 40% of the average annual income of salaried employees in Japan (National Tax Agency, 2019). Conventional distribution channels of fresh produce in Japan also pose challenges to smallholder farmers. These channels typically involve layers of middlemen, each requiring substantial handling fees and imposing constraints on quality (e.g., no ill-shaped produce), quantity, and types of fresh produce (MAFF, 2019). In Japan, the population of smallholder farmers is also rapidly aging with an average age of 69 years old in 2020 (MAFF, 2020). Compounding these challenges are the fewer numbers of the younger generation willing to enter the farming sector making it difficult for aging farmers to find successors (MAFF, 2019). Thus, the social innovation digital technology we examine through online social platforms is geared towards the poverty reduction of farmers.
We selected six platform companies for this study (see Table 1). These platforms were founded between 2015 and 2019 by entrepreneurial leaders with strong interests in helping smallholder farmers in Japan by forming online social networks to address their social problems of low income and lead to poverty reduction. The poverty of smallholder farmers is an old problem in Japan, and the digital platform solution is not a new solution either, but their match in the context of fresh produce transactions in Japan is new. Therefore, digital platforms of fresh produce in Japan represent an innovation.
Table 1. Selected online platforms
These entrepreneurs’ motivations came from their own experiences growing up in farming families or having had life-changing encounters with struggling farmers. All six platforms addressed the challenging low-income issue of smallholder farmers as part of their social missions. Additionally, some platforms, in their mission statements, also addressed the related problems of aging farmers and the unavailability of successors for the farm.
A key methodological challenge in an empirical study focusing on stakeholder mobilization is how to operationalize ‘stakeholder mobilization’, i.e., how to systematically observe, capture, and analyze ‘stakeholder mobilization’. In addressing this challenge, we obtained an extensive collection of ‘stakeholder actions’ in the form of who did what, and whenever available, to whom, and with what consequences. The key data source for such actions came from ‘chat systems’ that support online interactions primarily between farmers and consumers. We collected about 1,450 ‘chat threads’, where a chat thread consists of a ‘post’ that defines the thread’s topic, and responses that respond to the post or other responses.
The data based on ‘chat threads’ were augmented by the 14 semi-structured interviews, each lasting from 25 to 80 min, with an average of about 46 min per interview. Interviewees include the CEOs of the six platforms, platform staff, farmers, consumers, and vegetable connoisseurs. The interviews were audio recorded, and relevant parts were transcribed. To directly observe farmer-consumer interactions, one of the authors also attended two ‘meet-and-greet’ events for farmers and consumers and two offline farmers’ markets hosted by the platforms. The study also followed the data triangulation guideline promoted by Yin (Reference Yin2014) to ensure data accuracy and corroborate the information. Secondary sources include publicly available video materials, such as interview videos of platform CEOs and farmers, and various other secondary documents, such as government and institutional documents, corporate documents, and media documents (Bowen, Reference Bowen2009).
Operationalizing ‘Stakeholder Mobilization’
The first step to operationalize ‘stakeholder mobilization’ is to identify and collect observable stakeholder actions that may help drive the process of social innovation.
Unit of data collection
In this study, the unit of data collection is an ‘action’ in the form of ‘who’ (e.g., a farmer) did ‘what’ (e.g., shipping a produce package), and whenever available, to ‘whom’ (e.g., a consumer) with ‘what consequence/outcome’ (e.g., the consumer is satisfied with the package). A ‘stakeholder interaction’ is then a pair of ‘actions’, one of which is a response (response action) to the other (source action). It should be noted here that ‘actions’ are captured at a certain level of granularity to organize the large dataset, but actual ‘action instances’ that occur at a specific time and place were also collected to retain empirical details of ‘actions’.
For accuracy and consistency in capturing ‘actions’, we prepared a coding scheme (see Table 2), following acceptable practices (Weston, Gandell, Beauchamp, McAlpine, Wiseman, & Beauchamp, Reference Weston, Gandell, Beauchamp, McAlpine, Wiseman and Beauchamp2001). Although the importance of a coding scheme is well-noted for multi-coder consistency (Weston et al., Reference Weston, Gandell, Beauchamp, McAlpine, Wiseman and Beauchamp2001), one of the authors acted as the single coder in the coding process of extracting ‘stakeholder actions’ from the mountains of raw data over about 6 months. The coder was completing her doctoral dissertation, and dissertation committee members also verified the coding scheme. Throughout this time, the coding process and scheme mutually reinforced each other. More specifically, the coding scheme is both a means of the coding process and an outcome of the coding process.
Table 2. Coding scheme for identifying and collecting ‘actions’
The coder looked for specific constituents of a stakeholder action, such as ‘actor’, ‘action core’, ‘recipient’, and ‘consequence/outcome’, with various types for each constituent (see Table 2). For instance, ‘actor’ can be type ‘platformer’, ‘farmer’, ‘consumer’, ‘agricultural cooperative’, or ‘government office’ (Table 2). Throughout the analytical process, the coder was able to discover new ‘types’ (e.g., ‘resource creation’ as a new type for ‘Action Core’, ‘compromise’ as a new type for ‘Consequence/Outcome’) and identify various subtypes within each type as well. Subtypes of type ‘platformer’, for instance, are ‘platform CEO’, ‘platform staff’, ‘platform company’, and ‘vegetable connoisseur’ affiliated with a platform company (see Table 2).
As the coding scheme became more and more refined throughout the 6-month coding process, and the coder gained more experience in collecting stakeholder actions increasingly systematically, the coding also became more consistent across the various data sources gathered from the six different platforms. The coding scheme, therefore, played a significant role in promoting a systematic approach for analytical validity in this study.
Stakeholder tasks: ‘Five Cs’
Once the data collection unit is determined, individual ‘actions’ can be observed and collected. Actions can range from significant actions, such as a platform CEO identifying poverty issues facing smallholder farmers in Japan, to small, incremental actions, such as a consumer thanking the farmer for his spinach. We then map those actions into the five Cs stakeholder tasks, relying on Slaughter’s (Reference Slaughter2017) framework. The five Cs model enables us to systematically capture all relevant actions that led to eventual poverty reduction and helps us to identify more accurately which actions contributed to the social innovation process in what way.
Thus, our procedure to operationalize ‘stakeholder mobilization’ starts with the identification and collection of observable ‘actions’ and maps them into the five Cs stakeholder tasks. Thereby, the five Cs model enables us to unpack the social innovation process through a more micro lens of specific stakeholder actions.
Findings
Once all actions and corresponding action instances were collected, they were assigned to the five Cs tasks (i.e., Clarification, Curation, Connection, Cultivation, and Catalyzation). Table 3 shows representative actions and corresponding action instances for each task. Summary descriptions of the five tasks are given mostly in the context of the two successful platforms (Platforms A and B).
Table 3. Representative actions and corresponding action instances for the five tasks
Clarification
For the clarification task, the platform CEOs identified the poverty issues facing smallholder farmers in Japan. Then, the CEOs crafted and personally disseminated the goals and missions of their digital online platforms. Typically, the motivations behind their goals and missions came from their personal experiences, such as growing up in a farming family and having had life-changing encounters with smallholder farmers. All six CEOs in the study enthusiastically advocated the poverty of smallholder farmers in Japan as a serious social problem. The CEOs conveyed their goals and missions to use their innovative digital online platforms to address the serious low-income problem through various means, such as personal, direct communications with individual farmers, presentations at agricultural forum events, and, later, TV appearances. Initially, many farmers were skeptical of the CEOs and their online ideas, but through the CEOs’ persistence, many farmers positively responded to their messages.
Some CEOs also voiced related problems of aging farmers, the issue of the unavailability of successors, and the problem of limited farmer-consumer direct interactions. For instance, platform A’s CEO stated in an interview: ‘Consumers in the city…don’t know the situation with farmers in the countryside. There are only elderly farmers who can’t see the value their produce has. The farming community there is dying. Consumers might want to do something to help, but they don’t know anything. All they do is judge the prices of produce and consume. I wanted to directly connect farmers and consumers and create a future of Japan’s primary industry. If there’s no one to grow the produce, we can’t eat. If there’s no one to eat, farmers can’t survive. Farmers and consumers are bound together by a common destiny…and I want to connect them. That’s the mission’. Platform A’s CEO stressed that even a simple ‘Thank you for the food’ means a lot to many farmers and contributes to their willingness to continue farming despite various struggles. A farmer echoed: ‘There is one moment that I feel happiest. After many, many trial and error, over and over, from planting the seeds, to taking care of the plants for days, and then at long last, I create a vegetable that I envisioned. Then when the consumer writes in the chat threads, “It was delicious,” in that very moment, I think “Yoshi! (Good!)”.’
Curation
During the curation phase, the platforms’ recruiting was mostly through in-person visits to the farms and agricultural forum events by the CEOs or their staff. Platformers would appeal to farmers and consumers by emphasizing that digital online platforms are a viable solution to poverty. Here, the new matching between the social problem and the solution is a critical step of social innovation. However, not just any farmer could join as the platforms had a set of criteria for selecting farmers: e.g., farming as the main source of income, a certain practice on pesticide use, and willingness to interact online with consumers. Farmers must also be those who share the goals and missions of the platform.
Regarding consumer-recruiting, the platforms deployed various outlets such as television commercials, the platforms’ YouTube channels, and social networking services (Facebook, Twitter, Instagram, and Line). An apple farmer found one of the platforms through an economy magazine after struggling to find a better way to sell his produce to consumers (Platform B, Reference Platform B2024a). The platforms also tried to entice platform-visiting consumers to register by featuring, on their websites, some region-specific unique produce not available at supermarkets and some of their popular farmers who exercise certain extraordinary farming practices.
These recruiting efforts were the platforms’ main ongoing activities, with occasional new initiatives and campaigns. For instance, in 2020, Platform B launched a ‘Neighborhood Program’ to recruit older smallholder farmers struggling to make ends meet. These farmers were reluctant to use online technologies as they were unfamiliar with how to sell their produce online. Through the program, however, the older farmers can gather their produce within the neighborhood and bring them to the younger, already active members of Platform B and sell their produce together. Many farmers and consumers registered at the two successful platforms in response to these ongoing and new efforts. As of 2023, Platform A had around 7,900 registered farmers and 700,000 registered consumers (PR Times, 2023a) while Platform B had 9,100 registered farmers and 950,000 registered consumers (PR Times, 2023b). As an extension of the platforms’ efforts, some farmers also joined after hearing about the platform from other farmers in their local community. A vegetable farmer who received an award for their unusual spinach, which can be eaten raw, said he had heard of Platform B through his local egg producer, whom he trusts, and decided to join the platform (Platform B, Reference Platform B2024b).
Connection
The connection task has two streams of actions. First, the platforms prepare means of interactions among different stakeholders, most importantly, in this case, interactions between farmers and consumers. Then, in response, farmers, consumers, and platform staff build reasons for connection. Designing and constructing online digital platforms as an effective interaction space involves creative means of connection. The most prominent means of connection is online chat systems with user-friendly features to ease and promote interactions primarily between farmers and consumers who may not even live in the same prefecture. To this end, farmers and sometimes platform staff created detailed farmer profiles and product pages to attract consumers from all over Japan, increasing sales opportunities for struggling farmers. At Platforms A and B, farmer profiles had considerable leeway for farmers to express themselves, including space to upload photos of themselves, their farmers, or their livelihoods to convey better to consumers their dedication to quality despite tough financial situations. Consumers can view these photos and learn about the farmers, the produce, and the difficult farming situations, and thus, learn how their purchases can help farmers out of poverty in the long run.
In contrast, on the other platforms, these profiles had rigidly structured formats with limited space for just one or two photos. In both farmer profiles and produce pages, the photo qualities were significantly better at Platforms A and B than at other platforms.
As observed on Platform A, another means of connection was regularly held, such as meet-and-greet offline events, for farmers and consumers to meet and interact. In response to this means of connection, farmers often had to travel long distances from their rural areas to large cities where the events were usually held. On one occasion, a farmer of a specific white radish unique to his region (called ‘Numayama daikon’), drove with his family about eight hours from northwestern Akita prefecture to down to Tokyo. At the meet-and greet event he stated, ‘This was a great opportunity for me to meet with you and to spread the word in Tokyo and Kanto region about Numayama daikon and why it’s so special. I’m so happy to hear from you all and happy to have met you. Hearing your words makes me want to try hard and make Numayama daikon more popular’.
Cultivation
In the cultivation task, the stakeholders with shared goals interact and nurture trusting relationships. Platformers carefully crafted their mission statements to establish shared goals among smallholder farmers and consumers for their mutual trust. They also carefully selected farmers who are willing to communicate with consumers online. A variety of farmer-consumer interactions were initiated by consumers with genuine concerns or a sense of support towards farmers. For example, when an apple farmer from the northern region of Japan suffered severe loss from a major typhoon, some consumers sent messages of concern using the chat feature on the online platform and offered to purchase those typhoon-damaged apples so they would not go to waste and lead to financial loss for the farmer. In response, the farmer sent back a note of gratitude and introduced ‘apples with some bruising but still in good shape’ on his produce page, which sold out quickly. Some consumers, upon arrival of the package, tried an apple from the box and expressed in the chat comments that it tasted good, and others even added photos of apple pie or other dishes they made with the ‘imperfect apples’ saying they are looking forward to eating the dishes made with the farmer’s apples. If not through this digital online platform, this farmer would not have the chance to make such sales or directly hear the voices of the consumers.
However, trusting relationships are also cultivated by many stakeholder actions in the following catalyzation task. For example, every successful transaction, an interaction in the catalyzation task, is likely to generate and strengthen the sense of mutual dependability between farmers and consumers. Thus, while trusting relationships may enable transactions, such transactions, when successful, also nurture trusting relationships. Namely, trusting relationships and transactions (and possibly other actions in the catalyzation task) are mutually dependent.
Catalyzation
The catalyzation task aims to create value that aligns with the platforms’ goals and missions. The severe and widespread poverty issue of smallholder farmers is the most central and prominent problem addressed by the platforms, the value creation in the catalyzation task most critically means greater transactions between farmers and consumers. Of course, a greater size of a platform is likely to contribute to a greater volume of transactions at the platform. To illustrate, one platform has recorded about 3,750,000 visitors to its site per month. However, the issue of platform size is most directly addressed by the curation task, together with the clarification and connection tasks. Thus, what remains in the catalyzation task is the set of actions and interactions that create transaction-facilitating services beyond basic search-order-pay services.
A good example of such actions is recipe creation and suggestions by vegetable connoisseurs, platform farmers, and sometimes platform consumers themselves. These recipes were particularly valuable because the smallholder farmers’ produce was often unique and unfamiliar to the consumers. Such recipe creations and suggestions were far more active on Platforms A and B than on other platforms. For example, a vegetable farmer at Platform A produced a rare winter cauliflower, and a consumer bought it and made a special stew using the vegetable for family enjoyment.
As evidence that some farmers can sell in large quantities online and possibly at higher prices, the monthly revenues of top-selling farmers go beyond 14 million yen in a good month (Nihon Keizai Shimbun, 2021). A lemon farmer living in Hiroshima Prefecture on an island off the coast talks about how his selling-in-quantity problem changed since he began selling online. He said, ‘Sales had plateaued, and it was impossible to gain more sales so, there, I wondered “What shall I do?” and found [Platform B]’. According to the farmer, 80 percent of his sales are gained through that platform. He further said, ‘It is currently the biggest pillar for my income’.
As another example for farmers benefiting from the digital platform, a farmer on Platform B, had created a specialized apple called ‘pink lady®’ and introduced it on his profile. He said, ‘In the traditional distribution method, the marketing value lies in the “sweetness” and the “size”…Even if I invest in expensive facilities and spend a lot of time producing “pink lady®”, the price is the same as existing varieties. So, there is no way to tell if this apple has much of a fan base. However, once I started selling the apple on [Platform B], I sold more than 10,000 (one box = three kilograms of apples) and received over 700 comments. This told me that customers do, indeed, desire this variety’ (Platform B, Reference Platform B2024a). The farmer would not have found out such valuable information about consumers if he had not joined the platform.
Another example of transaction-facilitating services occurred when farmers and consumers faced a lot-size contention where farmers wanted to sell in larger quantities (seasonal, perishable produce). Still, consumers prefer to purchase in smaller quantities for their individual or family consumption. As for the challenge with such seasonal, perishable produce, Platforms A and B, but not other platforms, saw such lot-size contention as ‘creative tension’ (Jay, Reference Jay2013) and helped create various means of overcoming it. One such means was the idea of ‘seasonal variety packs’ which generally worked very well. One consumer made a warm pumpkin soup, a salad, and some steamed vegetables using all the autumn vegetables in the seasonal variety pack. The consumer mentioned that they were happy to have been able to ‘taste the autumn season’, and the vegetable farmer sold all his produce of the harvest season without letting any go to waste.
Discussion
In the previous section, we identified stakeholder actions for each of Slaughter’s five Cs using case data. Although the original model does not specify dependencies among the five Cs, some are intuitive. For example, Curation logically depends on Clarification, as recruiting network (i.e., digital online platform) members requires alignment with the network’s goals. A closer examination reveals a complex web of dependency relationships among the five Cs, suggesting that these interdependencies also drive the process of social innovation. In this section, we explore these dependencies and develop a more comprehensive model of what drives the process of social innovation in terms of stakeholder mobilization and how digital online spaces can reduce poverty for struggling stakeholders. We then use this model to explain why two platforms succeeded while four others failed and eventually terminated operations.
Stakeholder Mobilization Model
Based on our analysis of the five Cs and our qualitative analysis, we find that the stakeholder mobilization has two parts: (1) stakeholders joining the network (we call ‘Joining’), and (2) stakeholders in the network engaging in various tasks to promote the objectives of the network (we call ‘Engagement’). Among the five Cs, ‘clarification’ and ‘curation’ together represent ‘Joining’, whereas ‘connection’, ‘cultivation’, and ‘catalyzation’ collectively embody ‘Engagement’. Figure 1 summarizes the outcome of our attempt to identify all key dependencies among the five Cs and between the Joining and the Engagement parts. Each arrow in Figure 1 represents a relationship in which the arrow’s destination depends on the arrow’s source. We will briefly explain the arrows in Figure 1.
Figure 1. Stakeholder mobilization model
First, the arrow from Clarification to Curation seems straightforward. The effectiveness of recruiting stakeholders in the network (Curation) depends on how well the network’s objectives are clarified to the stakeholders. Platformers must advocate that the poverty issue is a serious social problem to the other stakeholders and also appeal to farmers and consumers that the new match between the social problem and the online platform solution is a critical step of social innovation. Many Clarification activities, such as mission postings on platform websites, occurred in preparation for recruiting, making it clear how the platform will address the poverty issue of smallholder farmers. Easy-to-understand graphics and/or videos were used to explain to consumers all over Japan the current distribution system for farmers and how the system can be a point of contention for smallholder farmers. Platformers use the current situation to contrast with their online system, using graphics again to make it clear how the farmers will benefit from using their online platforms.
On the other hand, while the arrow from Curation to Clarification is less obvious, Clarification may also depend on Curation for at least two reasons. One is realignment, and the other is reinforcement. In the case of realignment, it is admitted that some stakeholders, although already curated, may still stray from the mission of the network and their actions may have to be re-aligned with the mission via further clarification of the mission (Slaughter, Reference Slaughter2017: 187). In the case of reinforcement, some stakeholders who have already been curated may benefit from additional opportunities to reinforce their comprehension and appreciation of the mission. For example, in the meet-and-greet offline event hosted by a platform, most consumer participants are already registered members. Nevertheless, interacting with farmers face-to-face and listening to their personal farming stories may further clarify and deepen the consumers’ sense of the platform’s mission. However, it is important to note that the initial ‘meeting’ was online through the platform, and the consumers would not have known about the farmer at all if they had not been using the digital online platform nor would they have known about the meet-and-greet offline event.
Turning to the engagement side of the diagram, the arrow from Connection to Cultivation is apparent. Through the means of connections such as chat systems and meet-and-greet events, farmers and consumers will be mobilized to cultivate trusting relationships. For the farmers, creating a consumer fan base can directly affect the sales of their produce on the online platform, and a fan base can be deepened through further offline interactions. As a case in point, a vegetable and fruit farmer on Platform B became one of the most popular farmers after his meet-and-greet event, often selling all seasonal vegetable or fruit variety packs within the season. Clearly, the digital online platform has promoted him to new heights, which he would not have seen if he had solely been selling his produce through the offline distribution system or locally at farmers’ markets. Online distribution has enabled him to connect with consumers from outside his local area and all over Japan and cultivate trusting relationships with them.
Similarly, the arrow from Cultivation to Catalyzation naturally derives from the observation that actual farmer–consumer transactions (Catalyzation) are facilitated by their trusting relationships (Cultivation), particularly in the context of indirect, online transactions. Furthermore, the arrow from Catalyzation to Cultivation is similarly intuitive. For example, when an actual farmer–consumer transaction completes as expected, and the consumer truly enjoys the product, a sense of mutual trust is further cultivated between the two parties. Regarding the arrow from Cultivation to Connection, we argue that greater trusting relationships cultivated among farmers, consumers, and platformers are likely to underpin various activities of connection. For example, platforms promoting farmers who claim to sell pesticide-free produce critically depend on a mutual trust among the three parties. Consumers and platformers must trust the farmers’ word of growing pesticide-free produce, the consumer must trust the platform to be truthful in saying the farmers do actually sell pesticide-free produce, and farmers must also trust the platform to truthfully market the pesticide-free produce to consumers.
Finally, we discuss the pair of arrows between the joining and engagement sides. The arrow from the joining side to the engagement side is straightforward. The network must have some stakeholders already assembled to see their engagement in various activities. On the other hand, the arrow from the engagement side to the joining side is less apparent. A good example that illustrates this less intuitive arrow is Platform B’s ‘Neighborhood Program’. In general, Clarification and Curation are ongoing activities throughout the process. A big wave of Clarification and Curation can sometimes occur based on the outcome of Connection, Cultivation, and Catalyzation. More specifically, in the case of the ‘Neighborhood Program’, a group of older farmers reluctant to use online distribution systems were recruited through the support of the younger farmers in their local area who were already active members of the network.
Farmers have also joined through word-of-mouth. One spinach farmer joined after hearing about the online digital platform from an egg producer they trust. The spinach farmer said, ‘Since we don’t have a website, we use [Platform B] as our website to write about the value of our produce. It has become easier for us to explain and for [the consumers] to understand [the value]’ (Platform B, Reference Platform B2024b). The farmer used this opportunity to further engage with consumers and increase his online presence and sales.
Explanatory Power of the Model: Successful Versus Unsuccessful Platforms
Poverty reduction has scaling up and scaling deep dimensions (Bauwens, Huybrechts, & Dufays, Reference Bauwens, Huybrechts and Dufays2020; Smith & Stevens, Reference Smith and Stevens2019). Since this study focuses on the digital space, we refer to scaling up and scaling deep as ‘digital scaling up’ and ‘digital scaling deep’. Digital scaling up is where we must look at struggling Japanese smallholder farmers as a group. A large number of farmers can collectively benefit from digital platforms regarding poverty reduction. The issue of low-income farmers in Japan could be resolved. For digital scaling deep, we must now focus on the benefits to the individual farmer. Each struggling farmer will benefit more extensively if they join the digital platforms compared to when they had not joined. For example, one apple farmer will have access to a greater number of consumers than they had previously. They will make more sales, and maybe even be able to increase their farmland or upgrade their tools.
Digital scaling up and digital scaling deep also affect each other. Take Platform B’s Neighborhood Program, for example. Farmers already benefiting from the online platform helped their neighbors to join, thereby increasing the number of farmers. The platform recruiting more farmers to join (digital scaling up) means more variety in fresh produce and possibly more variety in ‘rare’ produce. Availability of unique produce will attract consumers interested in such produce (digital scaling deep for consumers). Some consumers have expressed that they joined the online platform to purchase a certain rare produce, which is only grown in their hometown. Both recruited farmers and consumers are not geographically constrained to one region in Japan because of the nature of the online platform, hence, their numbers are profoundly amplified. Farmer–consumer transactions over greater availability of produce including ‘rare’ produce will then result in a larger number of individual farmers being able to rise out of poverty (digital scaling deep). This phenomenon of scaling up and scaling deep affecting one another back and forth is known as cross-side network effects (Boudreau, Reference Boudreau2012; Song, Xue, Rai, & Zhang, Reference Song, Xue, Rai and Zhang2018). Such digital technologies directly addressing the social problems of stakeholders represent digital social innovation (Buck, Krombacher, Röglinger, & Körner-Wyrtki, Reference Buck, Krombacher, Röglinger and Körner-Wyrtki2023).
Among the six platform companies, two platforms (Platforms A and B) experienced success with digital scaling up and digital scaling deep, demonstrating cases of digital social innovation (e.g., Platform B’s Neighborhood Program), while the other four platforms (Platforms C, D, E, and F) encountered decline and eventual termination. The reason for such a rise and decline emerges through the differences between the two groups of platforms. Since the model delineates five stakeholder tasks, we first discuss how the two groups differ regarding individual Cs while considering cross-side network effects.
In Curation, successful platforms differ from the unsuccessful ones in two key points. Compared to the unsuccessful platforms, (1) the successful platforms have significantly actively utilized various media such as newspapers, social networking services, and television for their promotional activities, and (2) their promotional campaigns have stayed active throughout their operations rather than just the initial phase. Here, digital scaling up can be observed as hundreds and thousands of consumers are curated, and on successful online platforms, the number of consumer users continued to increase.
In Connection, the differences exist between the two groups, but they are subtle, as in the qualities of ‘chat systems’ and the richness of blog information on their websites. However, the significance of these subtle differences speaks volumes regarding the deep digital scaling. Richer information about the produce and the farmers in Connection may better facilitate farmer–consumer transactions for Catalyzation.
For Catalyzation, to facilitate farmer-consumer transactions, the successful platforms offered some support such as ‘seasonal variety packs’, ‘group purchasing’, and ‘recipe postings’, which the unsuccessful platforms did not provide or did provide but only in a very limited way. The successful platforms were more open to adaptation when contentions occurred (Sardana, Bamiatzi, & Zhu, Reference Sardana, Bamiatzi and Zhu2019).
Clarification and Cultivation are the only Cs with no striking differences between the six platforms. For Clarification, all six platforms’ CEOs used their prior experiences to realize their goals and missions (Sardana et al., Reference Sardana, Bamiatzi and Zhu2019). They made similar efforts to clarify those goals and missions to farmers and consumers. Similarly, Cultivation does not seem to have striking differences, yet it must be noted that successful transactions (Catalyzation actions) are likely to promote trusting relationships between farmers, consumers, and platformers.
Overall, the successful and unsuccessful platforms differ in some tasks, yet in other tasks, their differences seem to be nonexistent or rather insignificant. Thus, task-by-task comparisons of the two groups do not reveal a full story of their life-or-death differences. Hence, we now turn to the remaining part of the model, namely, the nonlinear dependencies among the five Cs. To illustrate this nonlinearity, let us consider the case of ‘seasonal variety packs’. The proposition of ‘seasonal variety packs’ was a consumer-centric idea as it offered the right quantities for individual or family consumption as opposed to the earlier practice of trying to sell a single product in a more-than-enough quantity, which garnered mild complaints from consumers who did not want to waste produce. This new practice of ‘seasonal variety packs’ is likely to increase consumers’ trust of farmers and of platforms in the sense that consumers may perceive farmers and platforms as willing to take actions to meet their needs.
With this increased sense of trust being circulated through chat systems, the farmers are now more likely to find new connections with new consumers from all over Japan who have never purchased ‘seasonal variety packs’. These intricate mutual reinforcements among Catalyzation, Cultivation, and Connection will further activate the Engagement part of the stakeholder mobilization. In fact, ‘seasonal variety packs’ became very popular among consumers, and the farmers typically sold out the season’s produce in a short period. Once the Engagement part becomes more active, the platformer can use it to promote its platform, possibly recruiting more consumers and farmers, and eventually resulting in greater transactions and leading to poverty reduction (Catalyzation). A case in point is the lemon farmer mentioned earlier, whose sales plateaued until he joined the online platform and effectively increased his income. Thus, the nonlinearity in the model can possibly close the loop (from Catalyzation to Catalyzation), suggesting positively spiraling cycles.
Within these cycles lies digital scaling up and digital scaling deep. Farmers earning a higher income may attract more farmers to the platform, leading to digital scaling up. More farmers imply more variety of produce, which can, in turn, attract more consumers for the farmers to sell to. Therefore, digital scaling up and digital scaling deep mutually reinforce each other on the successful platforms, a phenomenon also backed by recent literature on scaling social innovation using digital technologies (Mignoni, Bitencourt, Zanandrea, & Facco, Reference Mignoni, Bitencourt, Zanandrea and Facco2024).
In sum, the impacts of seemingly ‘small’ incremental actions can propagate throughout the nonlinear dependency cycles, as suggested by the model, and contribute to the eventual success of those platforms that are willing to take such incremental actions to lead smallholder farmers out of their low-income situation. Thus, the successful and unsuccessful platforms may differ only sporadically on individual Cs, but we argue that those on-and-off differences on individual Cs are sufficient to explain success–failure outcomes of the platforms due to the nonlinear dependency complexity of the five stakeholder tasks.
Implications for Poverty Reduction
We make several significant contributions to the literature on poverty reduction. Although previous research has examined the link between digital technologies and poverty reduction (Duvendack et al., Reference Duvendack, Sonne and Garikipati2023; Dzator et al., Reference Dzator, Acheampong, Appiah-Otoo and Dzator2023; Inoue, Reference Inoue2024; Lechman & Popowska, Reference Lechman and Popowska2022), most have done so using large-scale secondary data and have focused largely on lower income countries (Dzator et al., Reference Dzator, Acheampong, Appiah-Otoo and Dzator2023; Lechman & Popowska, Reference Lechman and Popowska2022). Poverty can occur even in high-income countries, and in this article, we looked at evidence through a micro lens and captured small, incremental efforts and actions of stakeholders that would directly or indirectly aim to reduce poverty for smallholder farmers in Japan. Furthermore, as mentioned at the outset, the process of ‘joint value creation’ is not well understood in stakeholder theory literature, and not many studies have such extensive empirical data. Many do not describe the whole process toward joint value creation from beginning to end. We provide detailed evidence of the stakeholder mobilization process, focusing on Slaughter’s (Reference Slaughter2017) framework, and show that small incremental efforts along specific Cs do matter because the interdependent five Cs tend to amplify those small efforts, as we discussed previously.
Second, most approaches on understanding stakeholder mobilization have emphasized linear processes. Existing studies have developed more schematic views on the process of social innovation, namely a dialectic scheme, a product innovation scheme, and a social change scheme. Ashta et al. (Reference Ashta, Couchoro and Musa2014) illustrate the ‘dialectic evolution’ in the context of microfinance, where the process of social innovation is seen as a linear chain of emergence and resolution of inter-stakeholder tensions. Bessant, Rush, and Trifilova (Reference Bessant, Rush and Trifilova2012) propose an ‘emergent process model’ of product innovation with five stages: (1) ‘crisis stage’, (2) ‘observatory stage’, (3) ‘laboratory stage’, (4) ‘prototype stage’, and (5) ‘scaling and diffusion stage’. This model frames social innovation as a linear process, moving from crisis identification to developing and disseminating scalable, product-focused solutions. Loogma, Tafel-Viia, and Ülmarik (Reference Loogma, Tafel-Viia and Ülmarik2013) describe social innovation as a ‘social change process’ with five stages: (1) ‘triggers’, (2) ‘goals’, (3) ‘change mechanisms’, (4) ‘social implications’, and (5) ‘social benefits’. This model views social innovation as a linear progression towards improved social conditions, driven by ‘change mechanisms’.
In contrast to the above approaches, our depiction of the process shows that firms may benefit from being aware of the interdependent nature of the five Cs when mobilizing their stakeholders for joint value creation. As seen in the studied cases, Clarification, Curation, and Connection strengthen both Cultivation and Catalyzation. Joint value creation is possible when the goal is clear and the suitable stakeholders are mobilized to connect and cultivate trust. Furthermore, our study provides evidence of significant iterations along many aspects of the five Cs rather than the typical linear process.
Third, and linked to the above, we also discussed critical differences between successful and failed platforms. Our findings show that the areas of Curation and Catalyzation played important roles in poverty reduction. The ‘Neighborhood Program’ for older smallholder farmers at Platform B is a case in point. The online platform’s innovative program directly impacted the relationships between younger and older farmers and brought change to the traditional distribution channel, leading to successful poverty reduction. Such findings add to recent research on digital poverty reduction (Si, Hall, Suddaby, Ahlstrom, & Wei, Reference Si, Hall, Suddaby, Ahlstrom and Wei2023), and provide an enhanced understanding of the specific success factors for digital online platforms to reduce poverty for struggling stakeholders.
Finally, we contribute indirectly to the digital inclusion literature on digital poverty reduction. Participation in any online platform requires smallholder farmers to learn new digital skills. For example, after joining during the Curation stage, farmers had to learn to cultivate an online presence and create their profiles, which would invite engagement from consumers. Furthermore, in the Cultivation stage, farmers had to learn how to interact with consumers through the online chat system. Additionally, they also had to develop social media marketing skills to advertise their products. As mentioned earlier, one apple farmer was able to sell slightly bruised apples after consumers voiced their concerns about the damage to the apples because of a typhoon. Such rapid responses required some level of social media skills on the part of these farmers. Finally, the mere act of participating in the platforms meant that the farmers had to become financially savvy. While we did not explore this issue, it is likely that such digital financial inclusion brought other advantages. Works by Duan, Yuan, and Tian (Reference Duan and Tian2024) and Shah (Reference Shah2025) suggest that financial inclusion can enable access to FinTech innovations such as mobile banking and peer-to-peer lending platforms. Access to financial services and loans at better rates can also reduce poverty.
Practical Implications, Limitations, and Future Research
As Dougherty (Reference Dougherty2018) emphasized, managers need to understand the ‘hows’ when it comes to practical implications. It should be noted that ‘small’ incremental efforts at individual tasks, such as recipe postings and seasonal variety packs, may gain rewards not only at the local level around specific tasks but also more extensively throughout the entire process, as the impacts of those efforts can propagate and potentially amplify throughout the nonlinear dependency cycles of five Cs. Thus, the leadership team of a social innovation project should not underestimate the competitive significance of ‘small’ incremental efforts and be well aware of the win–lose consequences of pursuing or not pursuing such inch-by-inch strategies. Even the smallest efforts from the leadership team can ripple across the network and through the process and ultimately make a large difference to the stakeholders involved.
Regarding the limitations of this study, as in case-based inquiries in general, the idiosyncratic features of the selected case setting might undermine the validity of the proposed model of the process of social innovation. For instance, the present study was conducted in the setting of social innovation in a business-driven private sector. Although the five Cs framework (Clarification, Curation, Connection, Cultivation, and Catalyzation) seems to be sector-independent, it is essential to test the validity of the proposed model in social innovation projects led by a public or a third sector, and possibly outside the food and agriculture domain to gain a more comprehensive understanding of the social innovation process with the five Cs framework applied. Exploring a different domain involving a different set of stakeholders may yield new insights. Furthermore, our qualitative study was limited to the developed nation of Japan. It is possible that the digital infrastructure in less developed countries, such as Bangladesh or Mozambique afflicted with more poverty, may not benefit as much from our findings. Nevertheless, since our study is focused on social innovation in the context of agriculture, our findings on stakeholder mobilization in the social innovation process may still be beneficial in the context of farming and the food industry in less developed countries whereby smallholder farmers face poverty.
Data availability statement
The data that support the findings of this study are available from the corresponding author, N. J. W. upon reasonable request.
Naomi Jane Wakayama (naomi.j.wakayama@gmail.com) is a Project Researcher at the Graduate School of Humanities and Social Sciences, Saitama University. She received her PhD from the University of Tokyo. Her research focuses on stakeholder relationships, the process of social innovation, and scaling social enterprises. She has presented her work at the International Association of Business and Society’s annual conference and published in Sustainability.
K. Praveen Parboteeah (parbotek@uww.edu) was the inaugural COBE Distinguished Professor at the University of Wisconsin – Whitewater. He is currently the Director of the Doctor of Business Administration program and Chair of the Management Department. His main research interests focus on cross-national issues, social issues in management, and innovation. He has published over 60 publications in the field’s top journals such as the Academy of Management Journal, Journal of International Business Studies, and Organization Science.
Youngwon Park (ywparkjp@gmail.com) is a Professor of the Faculty of Economics, Graduate School of Humanities and Social Sciences at Saitama University and an Endowed Chair Professor of the Management Education and Research Center at the University of Tokyo, Japan. His articles have been published in journals including the International Journal of Production Economics, International Journal of Technology Management, and Journal of Purchasing and Supply Management. His research focuses on technology management, global strategy and IT strategy, and global supply chain management.
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