Assessing the impact of big data on firm innovation performance: Big data is not always better data

2020 ◽  
Vol 108 ◽  
pp. 147-162 ◽  
Author(s):  
Maryam Ghasemaghaei ◽  
Goran Calic
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Parneet Kaur ◽  
Navneet Kaur ◽  
Paras Kanojia

Purpose Based on 9,281 firm-level survey data on micro, small and medium enterprises (MSMEs) in India, this study aims to investigate how access to different finance sources and collateral requirement facilitates the firm’s innovation activity across industries. Design/methodology/approach This paper used ordered logit regression models using Stata software for explanatory variables to measure the impact of explanatory variables on firm innovation performance. Firms’ innovation performance is measured through the aggregate innovation index obtained by adding up the no. of “new-to-firm” activities. Findings The empirical results reveal that external sources of funding impact innovation activity than other financing sources. Also, the requirement of collateral for financing impacts innovation performance significantly. This paper finds that firms funded by state-owned banks or government agency are more actively engaged in innovation activities. The firm’s size, ownership structure and location of the firm also show the varying innovation performance. This paper found variation in innovation performance across industries as well. Practical implications First, the present study underlines the significance of funding sources. Second, minimizing the need for collateral to obtain external finance boosts small firms’ innovation activity and will also trigger overall economic growth. Finally, while making policies for ownership transformation of state-owned institutions, policymakers should discuss these policies’ impact on innovative firms. Originality/value What facilitates innovation performance in an emerging market is missing in the literature for MSMEs, largely due to lack of data. It is reasonable not to generalize innovation knowledge in large firms to small firms because of the constraints, particularly MSMEs face.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Giulio Ferrigno ◽  
Giovanni Battista Dagnino ◽  
Nadia Di Paola

Purpose Drawing upon the importance of research and development (R&D) alliances in driving firm innovation performance, extant research has analyzed individually the impact of R&D alliance partner attributes on firm innovation performance. Despite such analyzes, research has generally underestimated the configurations of partner attributes leading to firm innovation performance. This research gap is interesting to explore, as firms involved in R&D alliances usually face a combination of partner attributes. Moreover, gaining a better understanding of how R&D partner attributes tie into configurations is an issue that is attracting particular interest in coopetition research and alliance literature. This paper aims to obtain a better knowledge of this underrated, but important, aspect of alliances by exploring what configurations of R&D alliance partner attributes lead firms involved in R&D alliances to achieve high innovation performance. To tackle this question, first, this study reviews the extant literature on R&D alliances by relying on the knowledge-based view of alliances to identify the most impactful partner attributes on firms’ innovation performance. This paper then applies a fuzzy set qualitative comparative analysis (fsQCA) to explore the configurations of R&D alliance partner attributes that lead firms involved in R&D alliances to achieve high innovation performance. Design/methodology/approach This study selects 27 R&D alliances formed worldwide in the telecom industry. This paper explores the multiple configurations of partner attributes of these alliances by conducting a fsQCA. Findings The findings of the fsQCA show that the two alternate configurations of partner attributes guided the firms involved in these alliances to achieve high innovation performance: a configuration with extensive partner technological relatedness and coopetition, but no experience; and a configuration with extensive partner experience and competition, but no technological relatedness. Research limitations/implications The research highlights the importance of how partner attributes (i.e. partner technological relatedness, partner competitive overlap, partner experience and partner relative size) tie, with regard to the firms’ access to external knowledge and consequently to their willingness to achieve high innovation performance. Moreover, this paper reveals the beneficial effect of competition on the innovation performance of the firms involved in R&D alliances when some of the other knowledge-based partner attributes are considered. Despite these insights for alliance and coopetition literature, some limitations are to be noted. First, some of the partners’ attributes considered could be further disentangled into sub-partner attributes. Second, other indicators might be used to measure firms’ innovation performance. Third, as anticipated this study applies fsQCA to explore the combinatory effects of partner attributes in the specific context of R&D alliances in the telecom industry worldwide and in a specific time window. This condition may question the extensibility of the results to other industries and times. Practical implications This study also bears two interesting implications for alliance managers. First, the paper suggests that R&D alliance managers need to be aware that potential alliance partners have multiple attributes leading to firm innovation performance. In this regard, partner competitive overlap is particularly important for gaining a better understanding of firm innovation performance. When looking for strategic partners, managers should try to ally with highly competitive enterprises so as to access their more innovative knowledge. Second, the results also highlight that this beneficial effect of coopetition in R&D alliances can be amplified in two ways. On the one hand, when the partners involved in the alliance have not yet developed experience in forming alliances. Partners without previous experience supply ideal stimuli to unlock more knowledge in the alliance because new approaches to access and develop knowledge in the alliance could be explored. On the other hand, this paper detects the situation when the allied partners are developing technologies and products in different areas. When partnering with firms coming from different technological areas, the knowledge diversity that can be leveraged in the alliances could drive alliance managers to generate synergies and economies of scope within the coopetitive alliance. Originality/value Extant research has analyzed individually the impact of R&D alliance partner attributes on firm innovation performance but has concurrently underestimated the configurations of partner attributes leading to firm innovation performance. Therefore, this paper differs from previous studies, as it provides an understanding of the specific configurations of R&D alliance partner attributes leading firms involved in R&D alliances to achieve high innovation performance.


Author(s):  
Arshad Muhammad ◽  
Chen Kun Yu ◽  
Aneela Qadir ◽  
Waqar Ahmed ◽  
Zahid Yousuf ◽  
...  

Purpose: This study aimed to investigate the big data analytics capabilities (BDAC) model using resource-based theory (RBT) and dimensions of big data analytics (management, technological, and talent) that influenced the firm innovation performance. Design/methodology/approach: The research uses quantitative research design where 548 respondents were selected for the survey from Pakistan electronic media regulatory authority (PEMRA), national database and registration authority (NADRA), and cellular companies. Only 394 useable responses were received from the respondents. Findings: The findings revealed that BDAC has a statistically positive impact on firm innovation performance. All of the proposed hypotheses were approved in this study. Research limitations/implications: The study gives future direction to the researchers and practitioners to implement this model in other industries. Practical implications: The research makes important theoretical and methodological contributions to the business and society's nexus in developing country firms that are under economic pressure. Originality/value: The paper is new in the context of the developing firm's innovation.


Author(s):  
Yanran Ma ◽  
Jianfeng Cai ◽  
Yiqi Wang ◽  
Umar Farooq Sahibzada

Based on information asymmetry, agency theory and resource-based view (RBV), this study investigates the impact of venture capital (VC) on venture firm innovation performance, ascertains the extent to which VC affects venture firm innovation performance and finds the mediating effect of management incentives. Constructing a sample of a novel panel dataset of firms listed on the SME Board of China, we examined a sample of 927 start-ups between 2008 and 2017, showing a notable negative relationship between VC and Patent, and a positive relationship between VC and total factor productivity (TFP), providing stable evidence that VC could not spur firm patent directly, but facilitate the commercialization of innovation. Moreover, it shows that management equity incentives (MEI) and management cash incentives (MCI) playing significant positive mediating role between VC and TFP, while there is no mediating effect between VC and Patent. Findings of this study strengthen the experience of VC and suggest how practitioners of SMEs to enhance the commercialization of innovation, considerably extends our understanding of the impact of VC on venture firm innovation performance.


2020 ◽  
Vol 21 (6) ◽  
pp. 1009-1034 ◽  
Author(s):  
Nima Garousi Mokhtarzadeh ◽  
Hannan Amoozad Mahdiraji ◽  
Ismail Jafarpanah ◽  
Vahid Jafari-Sadeghi ◽  
Silvio Cardinali

PurposeThe experience of successful firms has proven that one of the most important ways to promote co-learning and create successful networked innovations is the proper application of inter-organizational knowledge mechanisms. This study aims to use a resource-action-performance framework to open the black box on the relationship between networking capability and innovation performance. The research population embraces companies in the Iranian automotive industry.Design/methodology/approachDue to the latent nature of the variables studied, the required data are collected through a web-based cross-sectional survey. First, the content validity of the measurement tool is evaluated by experts. Then, a pre-test is conducted to assess the reliability of the measurement tool. All data are gathered by the Iranian Vehicle Manufacturers Association (IVMA) and Iranian Auto Parts Manufacturers Association (IAPMA) samples. The power analysis method and G*Power software are used to determine the sample size. Moreover, SmartPLS 3 and IBM SPSS 25 software are used for data analysis of the conceptual model and relating hypotheses.FindingsThe results of this study indicated that the relationships between networking capability, inter-organizational knowledge mechanisms and inter-organizational learning result in a self-reinforcing loop, with a marked impact on firm innovation performance.Originality/valueSince there is little understanding of the interdependencies of networking capability, inter-organizational knowledge mechanisms, co-learning and their effect on firm innovation performance, most previous research studies have focused on only one or two of the above-mentioned variables. Thus, their cumulative effect has not examined yet. Looking at inter-organizational relationships from a network perspective and knowledge-based view (KBV), and to consider the simultaneous effect of knowledge mechanisms and learning as intermediary actions alongside, to consider the performance effect of the capability-building process, are the main advantages of this research.


2021 ◽  
Vol 12 ◽  
Author(s):  
Lan Zhang ◽  
Biming Liang ◽  
Datian Bi ◽  
Yuan Zhou ◽  
Xiaohan Yu

Psychological research shows that as the main component of enterprise decision-making, CEOs are not completely rational, cognitive and psychological biases often influence their decision-making process. CEO narcissism has gradually attracted academic attention. Based on upper echelon theory and subconscious theory, this paper uses advanced artificial intelligence technology to quantify CEO narcissism as a kind of emotional intelligence. Taking A-share listed companies in China from 2010 to 2019 as research objects, this paper empirically tests the impact of CEO narcissism on debt financing and innovation performance. The results show that CEO narcissism has a significant positive impact on firm innovation performance. Debt financing plays a mediating role in the relationship between CEO narcissism and firm innovation performance. CEO narcissism can have a positive impact on firm innovation performance through debt financing. Compared with non-SOEs, SOEs' CEO narcissism has a more significant positive effect on debt financing and enterprise innovation performance. The research in this paper enriches psychology and organizational management and provides a reference for an enterprise's management decisions and for investors' investment decisions.


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