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This article empirically tests the impact of risk appetite of the executive team on the re-innovation strategy after technological innovation failure using a panel regression model from the perspective of regional financial development level of enterprises.

By means of time series global principal component analysis and panel regression model method, the study validated and analyzed the impact of risk appetite of the executive team on the re-innovation strategy after enterprise technological innovation failure.

The research found that the higher the risk appetite of executive team, the more inclined the enterprise is to choose the “focusing on quantity, ignoring quality” re-innovation strategy after technological innovation failure. The better the financial development level of the region where the enterprise is located, the better it can effectively reduce the re-innovation strategy of “focusing on quantity, ignoring quality” of the enterprise due to the high risk appetite of the executive team.

The findings of this study are helpful in improving the financial development level of the region where the enterprise is located. It can help the executive team of the enterprise to more objectively choose the innovation strategy after technological innovation failure, and reduce the phenomenon that the executive team of the enterprise only pays attention to the quantity of re-innovation and underestimates the quality of re-innovation after technological innovation failure due to its high risk appetite.

The purpose of this paper is to compare the effects of equity financing and debt financing on technological innovation, and prove that the enhancement of a financing system’s risk tolerance for technological innovation can enhance the innovation risk preference of enterprises and thus promote innovation.

This study is based on a transnational sample of 35 developed countries from 1996 to 2015, by using the panel econometric model to empirically examine the effects of two financing modes on innovation.

The findings showed that equity financing, which has higher risk tolerance, has a more positive impact on innovation than debt financing in terms of both economic uptrend and economic downtrend, and that government efficiency plays a significant role in supporting the performance of technological innovation.

The paper provides a research framework for examining how a financing system’s risk tolerance capacity affects the development of technological innovation through promoting risk preference among enterprises. This paper provides transnational and cross-cycle comparative evidence that equity financing with a strong risk tolerance capacity can better support technological innovation, even in periods of economic downtrend. Moreover, the importance of financing system’s risk tolerance capacity for innovation during economic crises is discussed.

The purpose of this conceptual paper is to name and categorize risks related to emerging technological innovations and to propose a number of countermeasures. The emphasis is placed on knowledge risks that are grouped under human, organizational and technological spheres and are presented from a small business perspective.

The presented paper takes into account the prior literature and the authors’ thoughts and experiences to identify potential knowledge risks and countermeasures.

Having a better overview of possible knowledge risks that may emerge in conjunction with the adoption and application of emerging technological innovations can help small businesses to better assess these new developments and their possible upsides and downsides. The proposed risks and countermeasures can also help policymakers as well as other organizations working for or together with smaller businesses to help them maintain and even increase their competitiveness.

Different implications are suggested for not only managers and employees in small businesses but also other stakeholders working for or with small businesses.

To the best of the authors’ knowledge, this paper is the first one that focuses on how small businesses can improve their decision-making regarding the adoption of new emerging technological innovation from a knowledge risk perspective.

The high uncertainty of technological innovation in megaprojects brings great challenges to the R&D institution and also acts as a trigger for moral hazard. The incentive and supervision are effective means to improve the performance of innovation. The purpose of this paper is to propose appropriate incentive and supervision mechanisms to reduce information asymmetry and improve the efficiency of incentives. Suggestions on technological innovation are put forward to megaprojects management.

According to the principal-agent theory, the research develops incentive models under three states, i.e. information symmetry, information asymmetry and information asymmetry based on supervision mechanism. The Bayesian theory is employed to prove the effectiveness of the novel supervision method based on risk assessment.

The results indicate that under the information asymmetry, the incentive intensity is positively correlated with the social benefits coefficient, and negatively correlated with the patent benefits coefficient. The R&D effort and the owner's incentive intensity decline with the increase of information asymmetry. The supervision of risks can effectively reduce the degree of information asymmetry, and the higher the uncertainty of innovations, the more significant the effect of supervision is. As the supervision intensity increases, the incentive intensity, the R&D effort and the innovation output will increase. In addition, the R&D institutions with high innovation capability, low unit cost of R&D and low risk-aversion are more willing to make efforts to innovate.

This study fills the research gap on incentive and supervision of technological innovation in megaprojects. The externality of innovation benefits is considered in the model. The traditional incentive model is extended through the introduction of supervision. Furthermore, a novel supervision method based on risk assessment is proposed. The results validate the importance of risk management in technological innovation and provide a new insight for project management.

Technological innovation is one of the strongest driving forces in the survival and growth of any organization, including textile and apparel industries. However, technological innovation inherits a wide array of risks due to the uncertainty involved in it. In-depth research reveals the existence of a significant relationship between innovation failures and the approach used to innovate, that is, the organization’s innovator type. However, quantitative evidence supporting this concern is still lacking. Hence, the purpose of this paper is to bridge the existing gap in the literature on effective management of technological innovation risk factors and the innovator type of textile and apparel industries.

The risk factors related to technological innovations are identified under different innovator types. Analytic network process (ANP) has been used to evaluate the contribution of risk factors according to the innovator type of the organization. Data was gathered through the literature review and structured and semi structured interviews with textile and apparel industry experts. The contribution of risk factors was determined through priorities, derived according to the ANP using Super Decision software.

Contribution of risk factors takes different values according to innovator type. This provides comprehensive knowledge on developing a risk management strategy according to the innovator type of the organization. Furthermore, this provides insight into the fact that a generalized risk management strategy will not be effective and sensible for all innovator types.

The findings provide a thorough understanding of developing a customized risk management strategy by determining the “most to least” criticality of risks based on the innovator type of the organization. Furthermore, findings can be used to adopt the most appropriate innovator type based on the organization’s key competencies. Moreover, this guides the organization in making the best use of internal resources during risk management. Furthermore, this provides insight into the risk factors that must be addressed prior to embarking on new innovative approaches.

Technological innovation has become a significant part of textile and apparel industries. To become distinguished from competitors, it is essential to harness the potentials of the organizations in achieving higher speeds, faster delivery times, more precise research and development processes followed by modern manufacturing techniques, lower inventory and lower costs. This paper aims to present the risk factors, root causes and their impact related to technological innovation. This uncovers deeper problems inherent to the technological innovation process while providing insight to develop a more robust risk management strategy in marking the survival and growth of the organizations in the textile and apparel trade.

Literature review and structured interviews with industry experts were conducted to identify the risk factors and root causes associated with technological innovations related to textile and apparel industries. The impact of root causes to the risk factors was determined through priorities, derived according to analytic network process using Super Decision software.

Impact of the root causes on risk factors take different priorities, highlighting the most alarming root causes, which contribute more to the outcome. This provides insight for a more precise decision-making on the order of prioritization of root causes in managing risks involved.

Findings of this research provide insight on the most influential competencies of any textile and apparel organization for a thriving innovation. Profound knowledge on risk factors, root causes and their contribution to the outcome enhances complex decision-making. This ultimately leads to “credible performances’’ of the technological innovation and optimizing the resources available, which bridges the gap that exists in the current literature.

The purpose of this paper is to present an integrated leapfrogging mode of technological innovation for developing countries or latecomer enterprises in a certain industrial innovation field. Furthermore, this paper discusses the basic paradigm of the integrated leapfrogging innovation, analyzes the risk in the integrated leapfrogging mode, and describes the risk map of the integrated leapfrogging mode. Finally, taking the example of the integrated leapfrogging mode of technological innovation in developing China High‐speed Railway, this paper carries out the simulation analysis by employing system dynamics model.

In order to examine the impact of the integrated leapfrogging innovation risk on innovative achievements, main risk variables need to be extracted from the process of the integrated leapfrogging innovation, based on the system simulation, relationships among different variables and the impact on innovative achievements can be obtained.

To prevent the risk of the integrated leapfrogging innovation across the innovation, the first thing we need to improve is the contractual relationship, which is to be fair and reasonable, according to the symmetry principles of risks and benefits, and to achieve risk‐sharing and revenue sharing, in addition, all parties must be clear about their responsibilities and interests. The second is the reasonable position of the government's behavior, and it hints that the government cannot interfere too much, and its function is to provide service and support instead of ordering. The third is that enterprises should effectively prevent the risk of the integrated leapfrogging innovation through risk identification and risk early warning and risk pre‐control approach.

A new concept of integrated leapfrogging mode of technological innovation has been put forward, and the risk map of the integrated leapfrogging mode has been described. In addition, this paper proposes some suggestions to prevent the risks of the integrated leapfrogging innovation for enterprises as a reference.

When developing a new product, a buying firm solicits revenue sharing bids from two competing suppliers. Bidding behaviors of suppliers do not always align with predictions from rational agent models due to task uncertainty and bounded rationality, which could result in non-optimal supplier offers and ultimately hurt buying firm interests. This paper aims to discuss the aforementioned issues.

The authors built an analytical model that considers the impact of supplier technological risk, buyer–supplier coordination cost and supplier loss aversion on the optimal bid of the supplier. Next, using limited information processing capacity as a theoretic lens, the authors explore antecedents to the size of a focal supplier's bidding error, the absolute difference between the actual bid and the optimal bid. The authors used quantitative lab experimental data to test the hypotheses.

(1) Bounded rational bidders often fail to differentiate between relevant and irrelevant competitive information when placing bids, (2) loss aversion of a bidder significantly affects not only levels of bids, particularly for bidders with competitive disadvantages, but also sizes of the bidding error and (3) competitive information that has clearer performance implications are more influential in reducing sizes of bidding errors.

The results provide a comprehensive view of the bidding behaviors of a bounded rational supplier in an innovation outsourcing context with competition. With the results, managers now have a better understanding of behavioral influencers behind non-optimal supplier bids in an innovation outsourcing context.

Based on dual information asymmetry, the two-stage segmented compensation mechanism for technological innovation of civilian enterprises’ participation in military (CEPIM) has been discussed.

On the basis of the traditional principal-agent problems, the incentive compatibility condition is introduced as well as the hybrid incentive compensation model is established, to solve optimal solution of the compensation parameters under the dynamic contract condition and the validity is verified by numerical simulation.

The results show that: (1) The two-stage segmented compensation mechanism has the functions of “self-selection” and “stimulus to the strong”, (2) It promotes the civilian enterprises to obtain more innovation benefit compensation through the second stage, (3) There is an inverted U-shaped relationship between government compensation effectiveness and the innovation ability of compensation objects and (4) The “compensable threshold” and “optimal compensation threshold” should be set, respectively, to assess the applicability and priority of compensation.

In this paper, through numerical simulation, the optimal solution for two-stage segmented compensation, segmented compensation coefficient, expected returns for all parties and excess expected returns have been verified under various information asymmetry. The results show that the mechanism of two-stage segmented compensation can improve the expected returns for both civilian enterprises and the government. However, under dual information asymmetry, for innovation ability of the intended compensation candidates, a “compensation threshold” should be set to determine whether the compensation should be carried out, furthermore an “optimal compensation threshold” should be set to determine the compensation priority.

The risks associated with digital innovation increasingly challenge value co-creation among stakeholders within the innovation ecosystem. Stakeholder collaboration is helpful in preventing risk occurrence. This study intends to explore the effects of different stakeholder collaboration strategies on risk prevention performance in a digital innovation ecosystem context.

A systematic literature analysis was first conducted to identify risk factors of digital innovation based on the technology–organization–environment (TOE) framework. Then, a bidimensional network model was constructed to visualize the collaborative relationships among stakeholders and the identified risks by focusing on a digital innovation case. The social network analysis method was applied to design stakeholder collaboration strategies from the ego and global network perspectives, and a simulation approach was conducted to evaluate the effects of the strategies on risk prevention performance.

The results validate the positive effect of stakeholder collaboration on risk prevention performance and reveal the important role of network reachability in formulating collaboration strategies. The strategy of strong–strong collaboration strategy can best enhance risk prevention performance like a “Matthew effect” in the digital innovation ecosystem.

First, risk identification based on the TOE framework provides a systematic list of risk factors for future digital innovation risk management research. Second, this study designs stakeholder collaboration strategies from a network perspective to enhance the understanding of the network status of each stakeholder and the network structure of the digital innovation ecosystem. Third, the simulation results reveal the effects of different collaboration strategies on risk prevention performance.