Abstract:Emerging economies can achieve substantial innovation with limited resources based on the analysis of demand (user needs) in contrast with the traditional RBV theory, which considers supply as the departure point of innovation.
“…These applications cover many sectors such as health (Beinare & McCarthy, 2011; Chui & Ko, 2020; Dako‐Gyeke, Amazigo, Halpaap, & Manderson, 2020; Mason, Barraket, Friel, O'Rourke, & Stenta, 2015), education (Kesküla, Loogma, Kolka, & Sau‐Ek, 2012; Siddike & Kohda, 2016; Yesufu & Alajlani, 2019), agriculture (Donkor, 2015; Rover, de Gennaro, & Roselli, 2017), energy (Maruyama et al, 2007), sport (Ratten, 2019; Svensson & Hambrick, 2019), tourism (Castro‐Spila, Torres, Lorenzo, & Santa, 2018; Kohler & Chesbrough, 2019; Walker & Chen, 2019), finance (Moore, Westley, & Brodhead, 2012; Moore, Westley, & Nicholls, 2012; Sinclair, McHugh, & Roy, 2019), transportation (von Schönfeld & Tan, 2019) and housing (Bouchard, 2011; Green & Vergragt, 2002; Lorek & Spangenberg, 2019). Furthermore, there are many other fields in which social innovation practices are examined such as entrepreneurship (Bhatt, Ahmad, & Roomi, 2016; Chan, Chui, Chan, & Yip, 2019; Datta, 2011; Farinha, Sebastiao, Sampio, & Lopes, 2020), local government (Cichorzewska & Cholewa‐Wiktor, 2015; Descubes et al, 2013; Edwards‐Schachter et al, 2012; Souza, Lessa, & Filho, 2019) and public policy (Alsudairi & Tatapudi, 2014; Berzin, Pitt‐Catsouphes, & Peterson, 2014; El‐Haddadeh et al, 2014; Sammut et al, 2020; von Jacobi, Edmiston, & Ziegler, 2017).…”
Section: Literature Reviewmentioning
confidence: 99%
“…Social innovations in general are rooted in social movements which result from new expectations and needs in the society (Descubes, Timsit, & Truong, 2013). To date, there have been various definitions of social innovation in the literature.…”
Since project management is inevitably a social effort involving all relevant actors, social aspects have to be emphasized when considering collaborative project management. Social innovation focuses on reacting to social demands and developing innovative solutions to overcome various social issues. Therefore, determining the social innovation potential in the project management process is very important. The main purpose of this study is to propose a Fuzzy Analytic Network Process (FANP) and Fuzzy VIKOR (FVIKOR)‐based decision model to determine the social innovation potential of technological projects. The results of FANP revealed that the most important criteria for determining social innovation potential of projects are financial resources, technological developments and social capital. Furthermore, FVIKOR was used for ranking social innovation potential of the selected technological projects. There are several managerial implications of this study. First, we suggest that practitioners should integrate the proposed model into their project evaluation processes. Second, they can also use this model to define the social innovation factors during project selection. Lastly, the proposed model can be employed to prioritize the social innovation factors that enable managers to allocate the appropriate resources to project management process.
“…These applications cover many sectors such as health (Beinare & McCarthy, 2011; Chui & Ko, 2020; Dako‐Gyeke, Amazigo, Halpaap, & Manderson, 2020; Mason, Barraket, Friel, O'Rourke, & Stenta, 2015), education (Kesküla, Loogma, Kolka, & Sau‐Ek, 2012; Siddike & Kohda, 2016; Yesufu & Alajlani, 2019), agriculture (Donkor, 2015; Rover, de Gennaro, & Roselli, 2017), energy (Maruyama et al, 2007), sport (Ratten, 2019; Svensson & Hambrick, 2019), tourism (Castro‐Spila, Torres, Lorenzo, & Santa, 2018; Kohler & Chesbrough, 2019; Walker & Chen, 2019), finance (Moore, Westley, & Brodhead, 2012; Moore, Westley, & Nicholls, 2012; Sinclair, McHugh, & Roy, 2019), transportation (von Schönfeld & Tan, 2019) and housing (Bouchard, 2011; Green & Vergragt, 2002; Lorek & Spangenberg, 2019). Furthermore, there are many other fields in which social innovation practices are examined such as entrepreneurship (Bhatt, Ahmad, & Roomi, 2016; Chan, Chui, Chan, & Yip, 2019; Datta, 2011; Farinha, Sebastiao, Sampio, & Lopes, 2020), local government (Cichorzewska & Cholewa‐Wiktor, 2015; Descubes et al, 2013; Edwards‐Schachter et al, 2012; Souza, Lessa, & Filho, 2019) and public policy (Alsudairi & Tatapudi, 2014; Berzin, Pitt‐Catsouphes, & Peterson, 2014; El‐Haddadeh et al, 2014; Sammut et al, 2020; von Jacobi, Edmiston, & Ziegler, 2017).…”
Section: Literature Reviewmentioning
confidence: 99%
“…Social innovations in general are rooted in social movements which result from new expectations and needs in the society (Descubes, Timsit, & Truong, 2013). To date, there have been various definitions of social innovation in the literature.…”
Since project management is inevitably a social effort involving all relevant actors, social aspects have to be emphasized when considering collaborative project management. Social innovation focuses on reacting to social demands and developing innovative solutions to overcome various social issues. Therefore, determining the social innovation potential in the project management process is very important. The main purpose of this study is to propose a Fuzzy Analytic Network Process (FANP) and Fuzzy VIKOR (FVIKOR)‐based decision model to determine the social innovation potential of technological projects. The results of FANP revealed that the most important criteria for determining social innovation potential of projects are financial resources, technological developments and social capital. Furthermore, FVIKOR was used for ranking social innovation potential of the selected technological projects. There are several managerial implications of this study. First, we suggest that practitioners should integrate the proposed model into their project evaluation processes. Second, they can also use this model to define the social innovation factors during project selection. Lastly, the proposed model can be employed to prioritize the social innovation factors that enable managers to allocate the appropriate resources to project management process.
“…A recent review of social innovation research finds that it is growing at an exponential rate and can be regrouped into four categories: (a) community psychology; (b) creativity research; (c) social and societal challenges; and (d) local development (van der Have & Rubalcaba, 2016). Yet, in a recent review of the different kinds of innovation, social innovation was not even mentioned as a distinct category (Geldes, Felzensztein, & Palacios‐Fenech, 2017) despite its presence in many different streams of literature (Bhatt & Altinay, 2013; Charalabidis, Loukis, & Androutsopoulou, 2014; Descubes, Timsit, & Truong, 2013; Novy & Leubolt, 2005; Phils, Deiglmeier, & Miller, 2008; Pol & Ville, 2009; Varadarajan, 2014). Very little research has been done on social innovation diffusion.Innovation success is environment dependent.…”
The diffusion of social innovation requires overcoming institutional resilience and ignorance of innovation. The forces of the marketing and development work of the organization managers may be unable to overcome the strength of the institutional framework. These institution brakes include soft norms such as values, ideology, and psychology, as well as hard norms such as regulations. Spurts in the diffusion of the innovation require exogenous crises to overcome the friction.
“…That is to say that it was found in the literature that it is important to start by assessing the diffusion speed of innovative technologies within the university in order to evaluate students' adoption of this technology and its impact of the learning environment (Levin, Stephan, & Winkler, 2012). Previous research findings provide evidence on the significance these factors on technology adoption (Eggers & Aseem, 2018;Irena et al, 2013;Jason et al, 2016) Thus, it is expected that:…”
Section: H4 There Is Positive Relationship Exists Between Observabilimentioning
Focusing on the emerging economy in the Middle East and North Africa (MENA) region, this paper seeks to examine and test the antecedents of technological innovation adoption in the higher education sector and its impact on the learning environment. This research focuses on the adoption of technological education tools by students, who are the main adopter of technology considered here. A rich model encompassing technology factors, university based factors as well as consumer based factors, is adopted in this research. The model is developed based on three sources that are: Roger’s (2003) innovation adoption model, The Resource -based view of the firm (RBV) and previous literature. The adopted conceptual model highlighted that the adoption decision is based on a combination of perceived attributes of the educational technology, inter-organization factors and consumer factors. Data was collected from a convenient sample of students from three types of universities; public, private and foreign. Thus, the model is testified drawing on the results of empirical work conducted on three top ranked universities in Egypt. It should be noted that Egypt is selected as the country of analysis as it presents the largest educational sector in the MENA region in terms of capacity and structure. Data collection resulted in 300 usable questionnaires. The research model has been tested using Structural Equation Modelling (SEM). Results indicate that attributes of the innovation, institutional factors and market orientation policy were found to have a significant direct impact on technology adoption by students in universities. These findings lead to managerial implications focusing on managing students’ expectations and enhancing the learning environment within the HEIs in the MENA region. The contribution of this research is both theoretical and empirical. At the theoretical level, this research presents a distinctive model that encompasses a wide diversity of factors (technology based, institution based and consumer based) factors to study a rapidly changing topic like technology adoption in an important sector which is the higher education sector. At the empirical level, this research covers three key universities in Egypt and presents important implications on factors to be focused on in order to increase the level of technology use in the higher education sector.
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