PurposeThe overall aim of this paper is to identify the human capital and organizational factors that facilitate knowledge supporting system to boost innovation in emerging markets. The innovative capability of organizations depends undoubtedly on how successful they are in the generation of knowledge, either via external acquisition or internal creation, and how organizational culture, management support and human capital factors are significant.Design/methodology/approachTo validate this phenomenon, a quantitative explanatory study was designed. Data collection was carried out through a questionnaire completed by 211 respondent of firms located in Mexico. During data analysis, structural equation modeling was implemented with the support of SmartPLS 3.0 to understand the moderating role of organizational factors and human capital between knowledge support system and innovativeness.FindingsThe findings show that it is fundamental to build theories grounded in the particular realities of Latin American countries. For instance, these results suggest that there are two paths of innovation in Mexico in which organizational and human factors play key but differentiated roles. On the one hand, organizational culture, top management support, commitment and openness to innovation are essential to building and maintaining a knowledge support system that enables innovation. Additionally, promoting people-oriented organizations is key to innovation. Human capital factors, such as collaborators' motivation, professional skills and the opportunity to learn, intensify the knowledge support system and innovative capability.Research limitations/implicationsThe main limitations of the study are that only Mexican firms have been analyzed, and it is not possible to generalize the results to other contexts. Additionally, we have not identified whether the organizations that participated in the study originated in Mexico or are global enterprises that operate in Mexico. It could be significant to analyze whether multinationals from other countries that are operating in Mexico are more committed to learning to innovate than Mexican firms and the differences in their knowledge generation activities.Practical implicationsThe results of this study invite: (1) Managers to develop strategic initiatives that systematically promote knowledge generation activities identifying external and internal activities that allow them to build and maintain a knowledge support system, (2) Organizations to promote collaborative spaces in which employees can work in teams and strengthen their social ties, identifying communication physical and virtual spaces to share new ideas, seek new ways of doing things, and explore new processes and activities. This process will be significant in a culture where resistance to change predefines how knowledge translates into innovation.Social implicationsThe improvement of collaborators skills must be accompanied by other policies to enhance the innovation and business environment including the modernization and expansion of infrastructure. It is fundamental that governments firms and universities jointly develop a research agenda that will lead to the identification of significant issues and the effectiveness of solutions to foster innovation in Mexico. Only a holistic approach is likely to help the country move up the value chain and become a knowledge economy. In fact innovation is seen as a social process of public sector organizations that promote knowledge infrastructure such as universities and the government agencies that produce knowledge.Originality/valueThese results suggest that there are two paths of innovation in Mexico in which organizational and human factors play a key but differentiated role. In Mexican firms, innovative capability is possible due to knowledge support systems built on organizational factors, and human capital factors, such as professional skills and motivation for opportunities to learn which intensify innovation.
The Prevention and Reduction of the Bullwhip Effect by Electronic Data Interchange and Collaborative Forecasting