The widespread use of digital technology has brought about changes in the nature of business competition (Nambisan, 2017). As a result, no organization can avoid being affected by digital transformation (Bharadwaj et al., 2013; Hess et al., 2016). Influenced by the COVID-19 pandemic, firms have accelerated the speed of digital transformation to improve operational efficiency, products, and services; comprehensively transform organizational structures, business models, and processes; and fundamentally refresh business strategy (Hess et al., 2016). From a theoretical perspective, digital transformation is defined as a process that improves an entity by triggering major changes in the entity’s attributes through a combination of information, computing, communication, and connection technologies (Fitzgerald et al., 2014; Günther et al., 2017). Although the integration of digital technology with the real-world economy can prove challenging, some enterprises have successfully overcome the difficulties related to business transformation and achieved good results (Lanzolla et al., 2021). Prominent examples include Tencent’s decentralization, Alibaba’s digital platform, and Jingdong’s digital retail. However, compared with native digital organizations, such as Amazon, Facebook, and Google, the digital transformation of formerly nondigital organizations may take longer and involve greater challenges (Zinder & Yunatova, 2016). Especially for traditional manufacturing enterprises, digital transformation brings both opportunity and risk, which may promote fundamental changes in organizational structure and business processes (Hess et al., 2016).

Within the process of firm-level digital transformation, cross-functional collaboration occurs (Maedche, 2016), which brings valuable ideas and suggestions based on the different knowledge backgrounds of employees (Jeppesen & Lakhani, 2010). Obtaining ideas from individuals with different prior knowledge is the key driver for stimulating employees’ innovation (Piezunka & Dahlander, 2015). However, varying opinions can cause cross-functionality conflicts during collaboration. For example, in most manufacturing companies, cross-functionality teams are set up temporarily, without breaking up the organization’s original structure and hierarchy (Lopes Pimenta et al., 2014). This limited reorganization means that in traditional manufacturing companies, cross-functional opinion conflicts are often presented in the form of minority dissent (Gebert et al., 2006). Minority dissent can stimulate the team’s processing of information (De Dreu & Weingart, 2003; de Wit et al., 2012), which may force team members to consider different points of view (Jehn, 1995). This can stimulate creative thinking (Chen et al., 2019; De Dreu, 2006) and idea generation (Farh et al., 2010), thus encouraging self-reflection by members and enhancing trust and understanding. However, others have argued that cross-functional teams may experience friction, hostility, and barriers to knowledge sharing, weakening the innovation potential of team employees (Cronin & Weingart, 2007). Thus, whether the increase in cross-functional collaboration brought about by digital transformation stimulates innovation at the individual level remains controversial in the literature.

To bridge the gap between firm-level digital transformation and individual-level innovative behavior, we proposed that minority dissent would act as a mediator. Digital transformation improves cross-functional communication within the organization, breaks up the organization’s original form, and endows cross-functional team members with a greater ability to search for knowledge. Using their unique professional experience, cross-functional team members can provide task-related knowledge; this enhances their self-confidence, increases minority opinion conflicts in decision making, and brings new external knowledge to employees, thus improving their innovation behavior. In other words, the minority dissent brought about by digital transformation will promote employees’ innovative behavior. This paper contributes to the literature on digitalization by considering the crucial role played by minority dissent in turning firm-level digital transformation into individual-level innovative behavior.

Literature Review and Hypotheses

Digital transformation may affect the innovative behavior of employees (Mauerhoefer et al., 2017). The use of information and knowledge-management tools can enhance employees’ skills and knowledge-management capabilities (Banker et al., 2006); for example, technologies such as big data, cloud computing, and social platforms have smoothed the exchange of internal knowledge, policies, and other information (Nwankpa & Roumani, 2016). Therefore, the use of digital technology in the coordination of business processes has eliminated structural barriers that may hinder employees from obtaining information, opportunities, and resources. By helping employees improve their own skills and management capabilities, digital technology enhances self-efficacy, improves internal incentives (e.g., self-awareness and self-confidence), makes employees feel that they are in control of their career trajectory, and enhances their motivation for innovation (Thomas & Velthouse, 1990). Widespread and multichannel access to knowledge resources is possible with the help of digitization. Employees can obtain the information they need about market changes by looking in only one location, and internal multilevel interactions enhance the rapid transmission of this knowledge within the organization (Sharma & Bansal, 2020). Extensive acquisition and exchange of information improves employees’ access to internal and external knowledge, as well as stimulating their innovative thinking and promoting the implementation of innovative behaviors (Nambisan et al., 2019). Most important, digital transformation removes structural barriers that might otherwise prevent the acquisition of innovative resources (Lanzolla et al., 2021). As a connected resource, digital technology improves the ability to acquire, control, and manage resources, helping to achieve resource collaboration and innovation within the organization (Verhoef et al., 2021). When employees’ ability to control resources is enhanced, more innovative resources can be developed (Leong et al., 2016).

For manufacturing companies, digital transformation can fundamentally reshape business behaviors (Oztemel & Gursev, 2020). Digitalization can break an enterprise’s original hierarchical structure and completely transform its business processes and standards. Therefore, flexible cross-functional teams are increasingly being generated (Nambisan et al., 2019). The establishment of cross-functional teams within the enterprise provides multichannel knowledge, which helps the enterprise produce more innovative solutions to deal with multifaceted, complex challenges (Hülsheger et al., 2009). Members of cross-functional teams have different professional backgrounds and may provide different strategies pertaining to innovation, or judge the market environment from different points of view, resulting in some members opposing the views, ideas, or procedures of other team members, which can lead to disputes and objections (Nemeth, 1986). Conflicts of opinion are conducive to improving the quality of strategic decision making. Different opinions will prompt members to consider issues from different perspectives (Dooley & Fryxell, 1999; Nijstad et al., 2014) and will also stimulate their cognitive effort (Nemeth, 1986), especially when a conflict of opinions manifests as a minority opposing the majority (Levine et al., 2017). The cross-functional collaboration in manufacturing companies is different from that originating in digital companies. In manufacturing companies, team members from the different functional departments will be assembled to form a certain group to conduct cross-functional collaboration (Doroudi & Sharafpour, 2017). Therefore, conflicts of opinion are often expressed in the form of minority dissent, wherein a smaller faction—such as an individual on the team—opposes a larger faction (McLeod et al., 1997). Compared to conflicts between larger factions, minority dissent poses less of a threat to the team, as it is less likely to escalate to relationship conflict and cause pressure between team members (Nemeth, 1986), while still promoting the creation of innovative behaviors by employees and teams (Nijstad et al., 2014).

Alongside the increase in cross-functional collaboration, the application of digital technology increases the organization’s overall response speed and enhances the knowledge-searching ability of employees (Noack & Jacobsen, 2021). With the increased digitization of enterprises, the number of innovative decisions employees need to deal with simultaneously increases, resulting in more opportunities for employee dissent (Li et al., 2021). In the past, it could be difficult for employees with no relevant background in a given field to understand how to approach creative problem-solving tasks, and to provide useful and relevant insights for the organization (Amabile et al., 1996). This is especially true in the case of cross-functional team members who are not familiar with the target project. The application of digital technology has changed this situation (Nadkarni & Prügl, 2021). By empowering employees with stronger knowledge resources and search capabilities, cross-functional members of a team who are unfamiliar with the objectives of innovation tasks can seek out knowledge that relates to previously unfamiliar target tasks. This knowledge acquisition allows cross-functional members to feel more confident in making suggestions to their teams (Fitzgerald et al., 2014).

Digital transformation has increased the probability of minority dissent, including from cross-functional team members, which promotes the improvement of employees’ innovative behavior (Wang et al., 2020). This facilitating effect is achieved in two ways: First, minority dissent prompts employees to actively access diverse knowledge sources (Mitchell & Boyle, 2021). Second, insights from different perspectives can inspire creativity and critical thinking in employees (Schulz-Hardt et al., 2006). Minority dissent provides different knowledge attributes, prompting employees to passively absorb more information and consider this information from other angles (Mitchell & Boyle, 2021). For example, interaction with the marketing department might help an employee to understand customers’ demands and potential areas of interest, and interacting with members of the technical department might enlighten the employee about potential problems and their technical solutions (Nguyen et al., 2018). Minority dissent prevents premature consensus and stimulates the team to look at problems differently (Dooley & Fryxell, 1999). Extensive contact, knowledge exchange, and questioning with those who hold differing opinions can stimulate divergent thinking (Curşeu et al., 2012), which is the driver of creative ideas. This helps employees to break conventional thinking patterns and consider creative ways to solve practical problems. Although the dissent may only be by a minority, regardless of whether the dissent is correct or the dissenting viewpoint is included in the final solution, it will nevertheless prompt divergent thinking and creativity (Nemeth, 1986). Organization members must exchange creative insights and then work together to transform these creative ideas into feasible methods, products, and services. Minority dissent may cause individuals to become creative and divergent in their thinking, which will translate into innovation, especially when group members exchange and process information and ideas in an open and critical manner, and jointly implement new ideas and insights (Nijstad et al., 2014). Disagreement can eliminate the harmful consequences of group thinking or seeking consensus (Janis, 1972).

In summary, in this paper we proposed that minority dissent would mediate the positive effect of firm-level digital transformation on individual-level innovative behavior. Specifically, we anticipated that digital transformation would reshape the business processes and organizational structure of manufacturing companies, which would cause cross-functional collaboration to become widespread, and that the information search ability of cross-functional members would be improved as a result of this digital transformation. Employees would then develop self-confidence in and more freely express their opinions. Differences in professional background among employees mean the opinions of cross-functional team members may appear in the form of minority dissent, which will inspire other employees to look at previous decisions from different perspectives. This knowledge promotes the exchange of opinions, prompts employees to change their perspectives, expands knowledge searches, and drives the creation of innovative behavior. Therefore, we proposed the following hypotheses:
Hypothesis 1: Digital transformation will have a positive impact on employee innovation behavior.
Hypothesis 2: Digital transformation will have a positive impact on minority dissent.
Hypothesis 3: Minority dissent will have a positive effect on employee innovation behavior.
Hypothesis 4: Minority dissent will mediate the impact of organization-level digital transformation on individual-level innovative behavior.

Method

Participants and Procedure

The participants consisted of 172 women (31.85%) and 368 men (68.15%). Among them, 43 were top managers (7.96%), 107 were mid-level managers (19.81%), 204 were first-line managers (37.78%), and 186 were staff without managerial positions (34.44%). In terms of level of education, 52 participants had completed some or all of a high school diploma (9.63%), 160 had graduated from junior college (29.63%), 233 held a bachelor’s degree (43.15%), and 95 held a master’s degree or higher (17.59%). With respect to age, 67 participants were aged under 30 (12.41%), 228 were between 31 and 40 years old (42.22%), 194 were between 41 and 50 years old (35.93%), and 51 were aged over 51 years (9.44%). Regarding participants’ number of working years, nine had worked for less than 1 year (1.67%), 37 had worked for between 1 and 3 years (6.85%), 57 had worked for between 3 and 5 years (10.56%), 140 had worked for between 6 and 10 years (25.93%), and 297 had worked for more than 10 years (55.00%).

Data were collected via random sampling. Participants came from large firms with over 500 employees in several manufacturing industries across China. As the research involved human participants, our study was reviewed and approved by the Ethics Committee of the School of Economics and Management, University of Electronic Science and Technology of China before the survey form was distributed. According to the requirements of national legislation and institutions, written informed consent was not required for this study; thus, we informed the participants of the research purpose and obtained their oral consent while we were at the firms to distribute the survey forms on the spot. The survey was conducted between November 2020 and April 2021. Of the 2,500 survey forms distributed, 1,254 were returned and 540 of these were considered valid (effective rate of return = 21.6%).

Measures

The measures were sourced from existing research and modified for the study purpose. Several pilot-scale surveys and in-depth interviews were conducted to examine the rationality and suitability of the items and constructs within the survey by providing feedback on item wording. According to respondent feedback, select items were modified to ensure participants fully understood their meaning. All survey items were translated from English into Chinese by one of the authors, who is fluent in both languages, and localized to ensure content validity. Constructs were measured using multiple items rated on a 5-point Likert scale ranging from 1 = strongly disagree to 5 = strongly agree.

Digital Transformation
The items relating to digital transformation were developed based on the concepts proposed by Bharadwaj et al. (2013) and Libert et al. (2016). Consistent with Vial (2019), digital transformation was assessed using three items to measure the transformation of digital technology in producing, manufacturing, and operating processes within the firms. An example item is ‘‘Our company is running a business process based on digital technology.” Cronbach’s alpha in this study was .88.

Minority Dissent
Minority dissent was measured using four items adopted from Nijstad et al. (2014). Participants were asked whether different opinions existed between each functional department on issues such as whether to adopt new technologies, explore new customer demands, adopt new manufacturing plans, or formulate a new financial budget. An example item is “A few (one or two) individuals disagree with other members on whether to use the existing technology or introduce new technology.” Cronbach’s alpha in this study was .86.

Innovative Behavior
Innovative behavior was measured using six items from Ng and Lucianetti (2016). Participants were asked about the tendency of different individuals within each department to propose original schemes, innovative ideas, new methods, and new applications. An example item is “I always come up with an original solution to the problem.” Cronbach’s alpha in this study was .84.

Control Variables
Participants’ gender, job position, level of education, age, and number of working years were controlled for. Dummy coding was used for gender, which was coded as 0 = female or 1 = male; job position, level of education, and age were coded from 1 to 4. For job position, 1 = top managers, 2 = mid-level manager, 3 = first-line manager, and 4 = staff member without managerial position. For level of education, 1 = high school, 2 = junior college, 3 = bachelor’s degree, and 4 = master’s degree or higher. Regarding age, 1 = under 30 years, 2 = between 31 and 40 years, 3 = between 41 and 50 years, and 4 = over 51 years. Number of working years was coded from 1 to 5 with 1 = less than 1 year, 2 = between 1 and 3 years, 3 = between 3 and 5 years, 4 = between 6 and 10 years, and 5 = more than 10 years.

Results

Common Method Variance

Because data were collected for different variables in the same survey, we used Harman’s single-factor test to assess the likelihood of common method variance affecting the results, by running a principal component analysis. This resulted in three different components explaining 66.36% of the variance, where the first component explained only 25.22%. Thus, common method variance was not a threat to the validity of this study.

Construct Validity

We performed a confirmatory factor analysis to assess the reliability and validity of the reflective measure. The measurement model, comprising the three factors of digital transformation, innovative behavior, and minority dissent, fitted the data satisfactorily, chi square/degrees of freedom (χ²/df) = 4.62, root mean square error of approximation (RMSEA) = .08, goodness-of-fit index (GFI) = .92, Tucker–Lewis index (TLI) = .92, confirmatory fit index (CFI) = .93. Thus, the measures demonstrated adequate reliability and convergent validity. According to the results of the χ² difference tests for all paired constructs, the three-factor model fitted the data significantly better than did either the two-factor or one-factor models, indicating satisfactory discriminant validity.

Descriptive Statistics and Correlation Coefficients

Next, we examined the descriptive statistics and discriminant validity of the study variables, as well as the fit of the entire model. Means, standard deviations, and correlations of the variables are presented in Table 1, where it can be seen that the square roots of the average variance extracted for each construct are all greater than each of the off-diagonal elements in the corresponding rows and columns. This implies that the three variables of digital transformation, minority dissent, and innovative behavior can be discriminated from each other.

Hypothesis Testing

Structural equation modeling was used to examine the study’s hypotheses. The results show that the proposed model provided a very good fit to the data, χ²/df = 4.62, RMSEA = .082, incremental fit index = .92, TLI = .92, CFI = .93. The significance of the mediating effect in the hypothesized model was tested by using the bootstrapping estimation procedure in Amos 22.0 (5,000 replications).

Table 2 shows the total, direct, and indirect effects of each path of structural equation modeling. First, the effects of digital transformation on innovative behavior were significantly positive with a 95% confidence interval (CI) excluding zero; thus, Hypothesis 1 was supported. Second, the effects of digital transformation on minority dissent were also significantly positive and the 95% CI for the effect did not include zero; thus, Hypothesis 2 was supported. Third, the effects of minority dissent on innovative behavior were significantly positive and the 95% CI for the effect did not include zero; thus, Hypothesis 3 was supported. Finally, the effect of the mediation model was significant with a 95% CI that did not include zero, whereas the effects of the paths for digital transformation and innovative behavior were weaker; thus, Hypothesis 4 was supported.

To further explain the effect of a firm’s digital transformation on individual innovative behavior and the mediating effect of minority dissent in this relationship, the coefficients of each path are illustrated in Figure 1.

Discussion

The objective of this paper was to explore how firm-level digital transformation affects individual-level innovative behavior through the mediator of minority dissent. We anticipated that digitalization would intensify minority dissent and, therefore, promote employees’ innovative behavior.

The findings make two main contributions to the existing literature: First, at the microlevel we found that digital transformation promotes the emergence of minority dissent. Although previous studies have examined the impact of digital transformation at the organizational level (Chanias et al., 2019; Nambisan et al., 2019), few have explored how digital technology affects the organization through individuals from a microperspective. Our findings suggest that digital technology contributes to individuals’ development and utilizing of knowledge resources, and that the improvement of knowledge ability stimulates the power of cross-functional members of a team to express their opinions, which enriches the antecedents of minority dissent. Although studies have found that dissent can cause conflicts that undermine the team’s collaborative process (De Dreu & Weingart, 2003; de Wit et al., 2012), minority conflicts brought about by digital transformation tend to be task conflicts, not relationship conflicts, which may accelerate the team’s information processing (de Wit et al., 2012). Therefore, dissent may have a positive effect on innovation (Mitchell & Boyle, 2021; Nijstad et al., 2014). Second, at the organizational level, our findings support the viewpoint that a small number of objections, that is, minority dissent, are essential and effective for firms’ innovation (Nijstad et al., 2014) in the process of digitalization. The irreversible trend of digital transformation in the manufacturing process enlarges the role of minority dissent between employees’ knowledge acquisition and output innovation, reduces the risk of minority dissent rising to relational conflict, and helps to overcome the limitations of factional conflict. Related to this, our results show that digital transformation of traditional manufacturing enterprises does increase innovation (Chanias et al., 2019). Although digital transformation can be difficult for traditional enterprises (Verhoef et al., 2021), it will improve the innovation capacity of these enterprises in the long run.

Regarding the practical implications of our findings, in the process of digital transformation, traditional manufacturing enterprises should pay attention to organizational restructuring and guide the opinions of cross-functional team members, which will help reshape the innovation interaction mode among employees and play a positive role in innovation in the process of digital transformation. The different opinions exposed by a few objections promote employees’ innovation, enhance the possibility of sharing opinions, encourage team members to think about the problem at hand from multiple perspectives, and increase the possibility of forming new ideas.

This paper has some limitations. Although we measured the variables with scales taken from the existing literature, in which it has been proposed that employees’ perception of the organizational environment can reflect the degree of organizational change to a certain extent (Caldwell et al., 2004; Maheshwari & Vohra, 2015), there is still a lack of objective indicators for the measurement of these variables. Future research could measure the variables using indicators such as the firm’s financial statements. Despite these limitations, our study has made contributions to the digital transformation research within manufacturing firms through providing feasible measurement indicators that form a valuable reference for future research.

Amabile, T. M., Conti, R., Coon, H., Lazenby, J., & Herron, M. (1996). Assessing the work environment for creativity. Academy of Management Journal, 39(5), 1154–1184.
https://doi.org/10.5465/256995

Banker, R. D., Bardhan, I., & Asdemir, O. (2006). Understanding the impact of collaboration software on product design and development. Information Systems Research, 17(4), 352–373.
https://doi.org/10.1287/isre.1060.0104

Bharadwaj, A., El Sawy, O. A., Pavlou, P. A., & Venkatraman, N. (2013). Digital business strategy: Toward a next generation of insights. MIS Quarterly, 37(2), 471–482.
https://doi.org/10.25300/MISQ/2013/37:2.3

Caldwell, S. D., Herold, D. M., & Fedor, D. B. (2004). Toward an understanding of the relationships among organizational change, individual differences, and changes in person-environment fit: A cross-level study. Journal of Applied Psychology, 89(5), 868–882.
https://doi.org/10.1037/0021-9010.89.5.868

Chanias, S., Myers, M. D., & Hess, T. (2019). Digital transformation strategy making in pre-digital organizations: The case of a financial services provider. The Journal of Strategic Information Systems, 28(1), 17–33.
https://doi.org/10.1016/j.jsis.2018.11.003

Chen, X., Liu, J., Yuan, Y., & Cui, X. (2019). The curvilinear effect of task conflict on idea generation: The mediating role of reflexivity and the moderating role of task complexity. International Journal of Conflict Management, 30(2), 158–179.
https://doi.org/10.1108/IJCMA-02-2018-0029

Cronin, M. A., & Weingart, L. R. (2007). Representational gaps, information processing, and conflict in functionally diverse teams. Academy of Management Review, 32(3), 761–773.
https://doi.org/10.5465/amr.2007.25275511

Curşeu, P. L., Schruijer, S. G., & Boroş, S. (2012). Socially rejected while cognitively successful? The impact of minority dissent on groups’ cognitive complexity. British Journal of Social Psychology, 51(4), 570–582.
https://doi.org/10.1111/j.2044-8309.2011.02023.x

De Dreu, C. K. W. (2006). When too little or too much hurts: Evidence for a curvilinear relationship between task conflict and innovation in teams. Journal of Management, 32(1), 83–107.
https://doi.org/10.1177/0149206305277795

De Dreu, C. K. W., & Weingart, L. R. (2003). Task versus relationship conflict, team performance, and team member satisfaction: A meta-analysis. Journal of Applied Psychology, 88(4), 741–749.
https://doi.org/10.1037/0021-9010.88.4.741

de Wit, F. R. C., Greer, L. L., & Jehn, K. A. (2012). The paradox of intragroup conflict: A meta-analysis. Journal of Applied Psychology, 97(2), 360–390.
https://doi.org/10.1037/a0024844

Dooley, R. S., & Fryxell, G. E. (1999). Attaining decision quality and commitment from dissent: The moderating effects of loyalty and competence in strategic decision-making teams. Academy of Management Journal, 42(4), 389–402.
https://doi.org/10.5465/257010

Doroudi, H., & Sharafpour, M. (2017). Influences of cross-functional collaboration on technology commercialization function regarding the role of knowledge creation and support of superior management [In Arabic]. Innovation Management Journal, 6(1), 45–72. https://bit.ly/3CSLpxV

Farh, J.-L., Lee, C., & Farh, C. I. C. (2010). Task conflict and team creativity: A question of how much and when. Journal of Applied Psychology, 95(6), 1173–1180.
https://doi.org/10.1037/a0020015

Fitzgerald, M., Kruschwitz, N., Bonnet, D., & Welch, M. (2014). Findings from the 2013 Global Executive Study and Research Project: Embracing digital technology: A new strategic imperative [Research report]. MIT Sloan Management Review. https://bit.ly/3mQl6Dh

Gebert, D., Boerner, S., & Kearney, E. (2006). Cross-functionality and innovation in new product development teams: A dilemmatic structure and its consequences for the management of diversity. European Journal of Work and Organizational Psychology, 15(4), 431–458.
https://doi.org/10.1080/13594320600826314

Günther, W. A., Mehrizi, M. H. R., Huysman, M., & Feldberg, F. (2017). Debating big data: A literature review on realizing value from big data. The Journal of Strategic Information Systems, 26(3), 191–209.
https://doi.org/10.1016/j.jsis.2017.07.003

Hess, T., Matt, C., Benlian, A., & Wiesböck, F. (2016). Options for formulating a digital transformation strategy. MIS Quarterly Executive, 15(2), 123–139.

Hülsheger, U. R., Anderson, N., & Salgado, J. F. (2009). Team-level predictors of innovation at work: A comprehensive meta-analysis spanning three decades of research. Journal of Applied Psychology, 94(5), 1128–1145.
https://doi.org/10.1037/a0015978

Janis, I. L. (1972). Victims of groupthink: A psychological study of foreign-policy decisions and fiascoes. Houghton Mifflin.

Jehn, K. A. (1995). A multimethod examination of the benefits and detriments of intragroup conflict. Administrative Science Quarterly, 40(2), 256–282.
https://doi.org/10.2307/2393638

Jeppesen, L. B., & Lakhani, K. R. (2010). Marginality and problem-solving effectiveness in broadcast search. Organization Science, 21(5), 1016–1033.
https://doi.org/10.1287/orsc.1090.0491

Lanzolla, G., Pesce, D., & Tucci, C. L. (2021). The digital transformation of search and recombination in the innovation function: Tensions and an integrative framework. Journal of Product Innovation Management, 38(1), 90–113.
https://doi.org/10.1111/jpim.12546

Leong, C. M. L., Pan, S.-L., Newell, S., & Cui, L. (2016). The emergence of self-organizing e-commerce ecosystems in remote villages of China: A tale of digital empowerment for rural development. MIS Quarterly, 40(2), 475–484.
https://doi.org/10.25300/MISQ/2016/40.2.11

Levine, S. S., Bernard, M., & Nagel, R. (2017). Strategic intelligence: The cognitive capability to anticipate competitor behavior. Strategic Management Journal, 38(12), 2390–2423.
https://doi.org/10.1002/smj.2660

Li, H., Wu, Y., Cao, D., & Wang, Y. (2021). Organizational mindfulness towards digital transformation as a prerequisite of information processing capability to achieve market agility. Journal of Business Research, 122, 700–712.
https://doi.org/10.1016/j.jbusres.2019.10.036

Libert, B., Beck, M., & Wind, Y. (2016). 7 questions to ask before your next digital transformation. Harvard Business Review, 60(12), 11–13. https://bit.ly/3m6XQR4

Lopes Pimenta, M., Lago da Silva, A., & Tate, W. L. (2014). Developing and managing cross-functional teams: A multi-case study of Brazilian manufacturing companies. Journal of Technology Management & Innovation, 9(2), 1–16.
https://doi.org/10.4067/S0718-27242014000200001

Maedche, A. (2016). Interview with Michael Nilles on “What makes leaders successful in the age of the digital transformation?” Business & Information Systems Engineering, 58(4), 287–289.
https://doi.org/10.1007/s12599-016-0437-1

Maheshwari, S., & Vohra, V. (2015). Identifying critical HR practices impacting employee perception and commitment during organizational change. Journal of Organizational Change Management, 28(5), 872–894.
https://doi.org/10.1108/JOCM-03-2014-0066

Mauerhoefer, T., Strese, S., & Brettel, M. (2017). The impact of information technology on new product development performance. Journal of Product Innovation Management, 34(6), 719–738.
https://doi.org/10.1111/jpim.12408

McLeod, P. L., Baron, R. S., Marti, M. W., & Yoon, K. (1997). The eyes have it: Minority influence in face-to-face and computer-mediated group discussion. Journal of Applied Psychology, 82(5), 706–718.
https://doi.org/10.1037/0021-9010.82.5.706

Mitchell, R., & Boyle, B. (2021). Understanding the role of profession in multidisciplinary team innovation: Professional identity, minority dissent and team innovation. British Journal of Management, 32(2), 512–528.
https://doi.org/10.1111/1467-8551.12419

Nadkarni, S., & Prügl, R. (2021). Digital transformation: A review, synthesis and opportunities for future research. Management Review Quarterly, 71(2), 233–341.
https://doi.org/10.1007/s11301-020-00185-7

Nambisan, S. (2017). Digital entrepreneurship: Toward a digital technology perspective of entrepreneurship. Entrepreneurship Theory and Practice, 41(6), 1029–1055.
https://doi.org/10.1111/etap.12254

Nambisan, S., Wright, M., & Feldman, M. (2019). The digital transformation of innovation and entrepreneurship: Progress, challenges and key themes. Research Policy, 48(8), Article 103773.
https://doi.org/10.1016/j.respol.2019.03.018

Nemeth, C. J. (1986). Differential contributions of majority and minority influence. Psychological Review, 93(1), 23–32.
https://doi.org/10.1037/0033-295X.93.1.23

Ng, T. W. H., & Lucianetti, L. (2016). Within-individual increases in innovative behavior and creative, persuasion, and change self-efficacy over time: A social–cognitive theory perspective. Journal of Applied Psychology, 101(1), 14–34.
https://doi.org/10.1037/apl0000029

Nguyen, N. P., Ngo, L. V., Bucic, T., & Phong, N. D. (2018). Cross-functional knowledge sharing, coordination and firm performance: The role of cross-functional competition. Industrial Marketing Management, 71, 123–134.
https://doi.org/10.1016/j.indmarman.2017.12.014

Nijstad, B. A., Berger-Selman, F., & De Dreu, C. K. W. (2014). Innovation in top management teams: Minority dissent, transformational leadership, and radical innovations. European Journal of Work and Organizational Psychology, 23(2), 310–322.
https://doi.org/10.1080/1359432X.2012.734038

Noack, A., & Jacobsen, H. (2021). Transfer scouts: From intermediation to co-constructors of new knowledge and technologies in Germany. Research Policy, 50(4), Article 104209.
https://doi.org/10.1016/j.respol.2021.104209

Nwankpa, J. K., & Roumani, Y. (2016, December 11–14). IT capability and digital transformation: A firm performance perspective [Paper presentation]. 37th International Conference on Information Systems, Dublin, Ireland. https://bit.ly/37IEPf8

Oztemel, E., & Gursev, S. (2020). Literature review of Industry 4.0 and related technologies. Journal of Intelligent Manufacturing, 31(1), 127–182.
https://doi.org/10.1007/s10845-018-1433-8

Piezunka, H., & Dahlander, L. (2015). Distant search, narrow attention: How crowding alters organizations’ filtering of suggestions in crowdsourcing. Academy of Management Journal, 58(3), 856–880.
https://doi.org/10.5465/amj.2012.0458

Schulz-Hardt, S., Brodbeck, F. C., Mojzisch, A., Kerschreiter, R., & Frey, D. (2006). Group decision making in hidden profile situations: Dissent as a facilitator for decision quality. Journal of Personality and Social Psychology, 91(6), 1080–1093.
https://doi.org/10.1037/0022-3514.91.6.1080

Sharma, G., & Bansal, P. (2020). Cocreating rigorous and relevant knowledge. Academy of Management Journal, 63(2), 386–410.
https://doi.org/10.5465/amj.2016.0487

Thomas, K. W., & Velthouse, B. A. (1990). Cognitive elements of empowerment: An “interpretive” model of intrinsic task motivation. Academy of Management Review, 15(4), 666–681.
https://doi.org/10.5465/amr.1990.4310926

Verhoef, P. C., Broekhuizen, T., Bart, Y., Bhattacharya, A., Dong, J. Q., Fabian, N., & Haenlein, M. (2021). Digital transformation: A multidisciplinary reflection and research agenda. Journal of Business Research, 122, 889–901.
https://doi.org/10.1016/j.jbusres.2019.09.022

Vial, G. (2019). Understanding digital transformation: A review and a research agenda. The Journal of Strategic Information Systems, 28(2), 118–144.
https://doi.org/10.1016/j.jsis.2019.01.003

Wang, H., Feng, J., Zhang, H., & Li, X. (2020). The effect of digital transformation strategy on performance: The moderating role of cognitive conflict. International Journal of Conflict Management, 31(3), 441–462.
https://doi.org/10.1108/IJCMA-09-2019-0166

Zinder, E., & Yunatova, I. (2016, June 22–24). Synergy for digital transformation: Person’s multiple roles and subject domains integration [Paper presentation]. 1st International Conference on Digital Transformation and Global Society, St. Petersburg, Russia.
https://doi.org/10.1007/978-3-319-49700-6_16

This work was funded by the National Natural Science Foundation of China (71772027

72002094)

and Humanities and Social Science Fund of Ministry of Education of China (20YJC630020)

and the High-level Talents Research Foundation Project (No. 950319146).

Yunqing Liu, Institute of Finance and Public Administration, Anhui University of Finance and Economics, No. 962, Caoshan Road, 233030 Bengbu, Anhui, People’s Republic of China. Email: [email protected]