The effect of social networking sites and absorptive capacity on SMES’ innovation performance
TL;DR: In this article, the role of social networking sites in relation to innovation and knowledge in small-to medium enterprises has been investigated, and recommendations are proffered as to what small-medium enterprises should do in order to enhance their innovativeness.
Abstract: The combination of knowledge and innovation has become a cornerstone among knowledge and labour intensive enterprises. A growing number of enterprises are defined as knowledge intensive entrepreneurship ventures that have been widely studied in relation to their eco-system. However only few research have addressed this phenomenon to enterprises digital eco-system by adopting mainly a qualitatively approach. We point out that the relevance of the digital eco-system focusing on the role of social networking sites in relationship to innovation and knowledge. The use of social networking sites can provide a wealth of information about individuals and their networks, which can be utilised for various business purposes. It enables enterprises to create online communities and share user-created content. Within this context, enterprises actively interact with external actors such as customers, public institutions, and other businesses to acquire and absorb external knowledge, and then generate innovation. To gain insights from the global economy, 215 small to medium enterprises from different sets of global enterprises, both knowledge-intensive (e.g. management consulting, marketing and advertising, ICT and related services, legal and technical services) and labour-intensive (such as high tech and electronics, food and beverage, and consumer durables), were analysed. Via the Partial Least Square-Path Modelling the relationships between social networking sites, absorptive capacity, and innovation performance were measured. Therefore, recommendations are proffered as to what small-medium enterprises should do in order to enhance their innovativeness. The research ends with conclusions and implications to both scholars and practitioners.
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Posted Content•
TL;DR: In this article, the authors reconceptualize the firm-level construct absorptive capacity as a learning dyad-level measure, relative absorptive capacities, and test the model using a sample of pharmaceutical-biotechnology R&D alliances.
Abstract: Much of the prior research on interorganizational learning has focused on the role of absorptive capacity, a firm's ability to value, assimilate, and utilize new external knowledge. However, this definition of the construct suggests that a firm has an equal capacity to learn from all other organizations. We reconceptualize the firm-level construct absorptive capacity as a learning dyad-level construct, relative absorptive capacity. One firm's ability to learn from another firm is argued to depend on the similarity of both firms' (1) knowledge bases, (2) organizational structures and compensation policies, and (3) dominant logics. We then test the model using a sample of pharmaceutical–biotechnology R&D alliances. As predicted, the similarity of the partners' basic knowledge, lower management formalization, research centralization, compensation practices, and research communities were positively related to interorganizational learning. The relative absorptive capacity measures are also shown to have greater explanatory power than the established measure of absorptive capacity, R&D spending. © 1998 John Wiley & Sons, Ltd.
335 citations
TL;DR: In this paper, the role of ICTs and big data in intra-and interorganizational ties and the consequent effects on enterprises' innovation performance is investigated via structural equation modeling (SEM).
Abstract: The literature suggests that increasing investments in information and communication technologies (ICTs), knowledge exchange and sharing help SMEs tackle the current global and dynamic environment. Given that much of the useful knowledge resides outside the enterprises’ boundaries, these technological tools foster the gathering of big data and information. Despite these premises, few studies have considered the role of ICTs and big data in intra- and inter-organizational ties and the consequent effects on enterprises’ innovation performance. The paper investigates whether ICTs oriented to intra-organizational (in-house research and development [R&D]) and inter-organizational (open innovation) processes improve SMEs’ innovation performance. Therefore, via structural equation modelling (SEM), the study analyses a sample of 239 knowledge-intensive SMEs located in Italy. The noteworthy results are that ICTs oriented to intra- and inter-organizational innovation processes improve both these processes in generating new products and/or services. On this basis, managerial and academic implications are provided, along with avenues for further research.
269 citations
Cites background from "The effect of social networking sit..."
...In the current demanding and competitive market, enterprises seek to exploit opportunities, using technologies (Del Giudice & Maggioni, 2014; Scuotto et al., 2017) to achieve changes and creative destruction (Chesbrough, 2003; Gemünden, Salomo, & Hölzle, 2007)....
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TL;DR: The empirical research was conducted on 175 small to medium enterprises in the United Kingdom, suggesting that the knowledge-driven approach is the strongest determinant, leading to a preference for informal inbound OI modes.
Abstract: Purpose
This paper aims to investigate three key factors (i.e. cognitive dimensions, the knowledge-driven approach and absorptive capacity) that are likely to determine the preference for informal inbound open innovation (OI) modes, through the lens of the OI model and knowledge-based view (KBV). The innovation literature has differentiated these collaborations into informal inbound OI entry modes and formal inbound OI modes, offering an advocative and conceptual view. However, empirical studies on these collaborations are still limited.
Design/methodology/approach
Building on the above-mentioned theoretical framework, the empirical research was performed in two stages. First, data were collected via a closed-ended questionnaire distributed to all the participants from the sample by e-mail. Second, to assess the hypotheses, structural equation modelling (SEM) via IBM® SPSS® Amos 20 was applied.
Findings
The empirical research was conducted on 175 small to medium enterprises in the United Kingdom, suggesting that the knowledge-driven approach is the strongest determinant, leading to a preference for informal inbound OI modes. The findings were obtained using SEM and are discussed in line with the theoretical framework.
Research limitations/implications
Owing to the chosen context and sector of the empirical analysis, the research results may lack generalisability. Hence, new studies are proposed.
Practical implications
The paper includes implications for the development of informal inbound OI led by knowledge-driven approach.
Originality/value
This paper offers an empirical research to investigate knowledge-driven preferences in informal inbound OI modes.
260 citations
TL;DR: While most papers investigated the factors that drive social media adoption and use by entrepreneurs, it was found that the use of social media by entrepreneurs had transcended marketing and it is now used in business networking, information search and crowdfunding for their business.
215 citations
TL;DR: In this article, a systematic literature review was conducted to identify research trends and gaps in the field, conceptualize current paradigmatic views and therein provide clear propositions to guide future research.
180 citations
Cites background from "The effect of social networking sit..."
...…management literature and several scholars have identified the enabling role of social media in managing knowledge flows across internal (Brzozowski, 2009; Inkinen et al., 2015; Scuotto et al., 2017a) and external stakeholders (Adams, 2014; Callaghan, 2016; Filieri, 2013; Hitchen et al., 2017)....
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...Some researchers (Du et al., 2016; Scuotto et al., 2017a) have explored the role of users/customers as social media participants while some have explored the role of business communities (Hitchen et al., 2017) and employees (Dahl et al., 2011)....
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...This suggests a shift in acceptance (at least within the research community) of the wider role of Web 2.0 technologies such as social media in managing innovation activities (Palacios-Marqués et al., 2015; Scuotto et al., 2017a; Wikström and Ellonen, 2012)....
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...Increasingly, firms are experimenting new ways to leverage the widely distributed knowledge sources to improve innovation performance (Scuotto et al., 2017a)....
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...The increasing involvement of stakeholders in the firm's innovation processes coupled with increasing cost, speed and processing efficiency of ICTs has further encouraged firms to invest in social media tools (Mangold and Faulds, 2009; Scuotto et al., 2017c)....
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References
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Book•
01 Jan 1962
TL;DR: A history of diffusion research can be found in this paper, where the authors present a glossary of developments in the field of Diffusion research and discuss the consequences of these developments.
Abstract: Contents Preface CHAPTER 1. ELEMENTS OF DIFFUSION CHAPTER 2. A HISTORY OF DIFFUSION RESEARCH CHAPTER 3. CONTRIBUTIONS AND CRITICISMS OF DIFFUSION RESEARCH CHAPTER 4. THE GENERATION OF INNOVATIONS CHAPTER 5. THE INNOVATION-DECISION PROCESS CHAPTER 6. ATTRIBUTES OF INNOVATIONS AND THEIR RATE OF ADOPTION CHAPTER 7. INNOVATIVENESS AND ADOPTER CATEGORIES CHAPTER 8. DIFFUSION NETWORKS CHAPTER 9. THE CHANGE AGENT CHAPTER 10. INNOVATION IN ORGANIZATIONS CHAPTER 11. CONSEQUENCES OF INNOVATIONS Glossary Bibliography Name Index Subject Index
38,750 citations
TL;DR: In this paper, the authors argue that the ability of a firm to recognize the value of new, external information, assimilate it, and apply it to commercial ends is critical to its innovative capabilities.
Abstract: In this paper, we argue that the ability of a firm to recognize the value of new, external information, assimilate it, and apply it to commercial ends is critical to its innovative capabilities. We label this capability a firm's absorptive capacity and suggest that it is largely a function of the firm's level of prior related knowledge. The discussion focuses first on the cognitive basis for an individual's absorptive capacity including, in particular, prior related knowledge and diversity of background. We then characterize the factors that influence absorptive capacity at the organizational level, how an organization's absorptive capacity differs from that of its individual members, and the role of diversity of expertise within an organization. We argue that the development of absorptive capacity, and, in turn, innovative performance are history- or path-dependent and argue how lack of investment in an area of expertise early on may foreclose the future development of a technical capability in that area. We formulate a model of firm investment in research and development (R&D), in which R&D contributes to a firm's absorptive capacity, and test predictions relating a firm's investment in R&D to the knowledge underlying technical change within an industry. Discussion focuses on the implications of absorptive capacity for the analysis of other related innovative activities, including basic research, the adoption and diffusion of innovations, and decisions to participate in cooperative R&D ventures. **
31,623 citations
"The effect of social networking sit..." refers background in this paper
...From a theoretical point of view, management scholars identified two categories of absorptive capacity (Cohen and Levinthal 1990; Lane and Lubatkin 1998): (1) Potential absorptive capacity (Fosfuri and Tribó 2008) and (2) realised absorptive capacity (Jansen et al. 2005)....
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...Global enterprises use all of these digital platforms in order to enhance their absorptive capacity that, as previously stated, concerns in the process of a combination between external and internal knowledge (Audretsch et al. 2014; Cohen and Levinthal 1990)....
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...As stated by Cohen and Levinthal (1990), absorptive capacity enables enterprises to acquire, transfer, and assimilate external knowledge within the organisation and then generate new ideas....
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...absorptive capacity (Cohen and Levinthal 1990; Lane and Lubatkin 1998): (1) Potential absorptive capacity (Fosfuri and Tribó 2008) and (2) realised absorptive capacity (Jansen et al....
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...That is because enterprises need to intensify their capacity to absorb external knowledge mainly from the virtual environment and combine it with the internal knowledge (Cohen and Levinthal 1990)....
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Book•
01 Jan 2001
TL;DR: In this paper, the authors reviewed the literature on qualitative and quantitative research in social research and discussed the nature and process of social research, the nature of qualitative research, and the role of focus groups in qualitative research.
Abstract: PART ONE ; 1. The nature and process of social research ; 2. Social research strategies: quantitative research and qualitative research ; 3. Research designs ; 4. Planning a research project and formulating research questions ; Getting started: reviewing the literature ; 6. Ethics and politics in social research ; PART TWO ; 7. The nature of quantitative research ; 8. Sampling in quantitative research ; 9. Structured interviewing ; 10. Self-administered questionnaires ; 11. Asking questions ; 12. Structured observation ; 13. Content analysis ; 14. Using existing data ; 15. Quantitative data analysis ; 16. Using IBM SPSS for Windows ; PART THREE ; 17. The nature of qualitative research ; 18. Sampling in qualitative research ; 19. Ethnography and participant observation ; 20. Interviewing in qualitative research ; 21. Focus groups ; 22. Language in qualitative research ; 23. Documents as sources of data ; 24. Qualitative data analysis ; 25. Computer-assisted qualitative data analysis: using NVivo ; PART FOUR ; 26. Breaking down the quantitative/qualitative divide ; 27. Mixed methods research: combining quantitative and qualitative research ; 28. Writing up social research
17,352 citations
Book•
21 Jul 2011
TL;DR: Structural Equation Models: The Basics using the EQS Program and testing for Construct Validity: The Multitrait-Multimethod Model and Change Over Time: The Latent Growth Curve Model.
Abstract: Psychology is a science that advances by leaps and bounds The impulse of new mathematical models along with the incorporation of computers to research has drawn a new reality with many methodological progresses that only a few people could imagine not too long ago Such progress has no doubt revolutionized the panorama of research in the behavioral sciences Structural Equation Models are a clear example of this Under this label are usually included a series of state-of-the-art multivariate statistical procedures that allow the researcher to test theoryguided hypotheses with clearly confi rmatory ends as well as to establish causal relations among variables Confi rmatory factor analysis, the study of measurement invariance, or the multitraitmultimethod models are some of the procedures that stem from this methodology In this sense, it would be diffi cult to fi nd a scientifi c journal that publishes empirical works in psychology that does not address some of these issues, so their current transcendence is undeniable The manual written by the Full Professor of the University of Ottawa, Barbara M Byrne, is a link in a series of books that address this topic Throughout her long academic trajectory, Professor Byrne developed interesting and popular work focused on bringing the researcher and the professional layman—and not so layman—closer to the diverse statistical programs available on the market for data analysis from the perspective of structural equation models (ie, LISREL, AMOS, EQS) (Byrne, 1998, 2001, 2006) Bearing this in mind, the main goal of this work is to introduce the reader to the basic concepts of this methodology, in a simple and entertaining way, avoiding mathematical technicisms and statistical jargon For this purpose, we used the statistical program Mplus 60 (Muthen & Muthen, 2007-2010), an extremely suggestive software that incorporates interesting applications The authoress provides a practical guide that leads the reader through illustrative examples of how to proceed step by step with the Mplus, from the initial specifi cations of the model to the interpretation of the output fi les On the one hand, we underline that the data used proceed from prior investigations and can be consulted in the Internet, offering the reader the possibility of practicing with them (http://wwwpsypresscom/sem-with-mplus/ datasets/); on the other hand, updating the information with novel and apt bibliographic references allows the reader to study in more depth the diverse topics that are presented in the manual, if he or she so desires The book consists of four sections, with a total of 12 chapters The fi rst section, Chapters 1 and 2, addresses introductory terms related to structural equation models and working with the Mplus program at a user-level The second unit focuses on data analysis with a single group In Chapter 3, the factor validity of the self-concept is tested by means of confi rmatory factor analysis In Chapter 4, the authoress performs a fi rst-order confi rmatory factor analysis, in which she examines the validity of the scores of the Maslach Burnout Inventory (MBI) in a sample of teachers In Chapter 5, the internal structure of the scores on the Beck Depression Inventory-II is analyzed by means of second-order confi rmatory factor analysis in a sample of Chinese adolescents In the next chapter, the complete model of structural equations is tested, and the authoress examines the causal relation established between diverse variables (ie, work climate, self-esteem, social support) and Burnout The third section of the manual is, in my opinion, the most interesting, not only because of the expansion of the study of measurement invariance in recent years but also because of the expansion it may possibly have in the future In this section, Professor Byrne goes into multigroup comparisons Specifi cally, in Chapter 7, she examines the factor equivalence of the MBI in two samples of teachers by means of the analysis of covariance structures In this chapter, she introduces relevant concepts, such as types of invariance (confi gural, metric, and strict) or the invariance of partial measurement In Chapter 8, she also analyzes measurement invariance, using for this purpose the analysis of mean and covariance structures This analysis, in comparison to the analysis of covariance structures, allows contrasting the latent means of two or more groups With this goal, she verifi es whether there is measurement invariance between the scores on the Self-description Questionnaire-I in Nigerian and Australian adolescents In Chapter 9, she proposes a complete model of structural equations in which she tests the causal structure through the procedure of cross validation Lastly, in the fourth section, she reveals three very interesting topics, that are also up-to-date and that, to some degree, go beyond the initial goal of the book, such as the multitrait-multimethod models, latent growth curves, and multilevel models Summing up, the work “Structural Equation Modeling with Mplus: Basic concepts, applications, and programming” is of enormous interest and utility for all professionals of psychology and related sciences who, without having exhaustive knowledge of the details of structural equation models, wish to test their hypothetical models by means of the Mplus program No doubt, this is a reference manual, a must-read that is accessible and that has a high degree of methodological rigor We hope that the readers
16,616 citations
"The effect of social networking sit..." refers background or methods in this paper
...…et al. 2008), on the other hand, measures the positive or negative connection among LVs. Unlike traditional multivariate procedure, PLS provides explicit and estimated error of variance parameters (Byrne 2013), and is able to examine more than one regression equation/relationship at the same time....
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...error of variance parameters (Byrne 2013), and is able to examine more than one...
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