How attitudes, vision and ability to capture opportunities affect startups’ business creativity

Copyright © 2020 The Author(s). Published by VGTU Press This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons. org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. *Corresponding author. E-mail: joseramon.saur[email protected] Creativity studies ISSN 2345-0479 / eISSN 2345-0487 2020 Volume 13 Issue 2: 387–405 https://doi.org/10.3846/cs.2020.10482 HOW ATTITUDES, VISION AND ABILITY TO CAPTURE OPPORTUNITIES AFFECT STARTUPS’ BUSINESS CREATIVITY Pedro PALOS-SANCHEZ 1, José Ramón SAURA 2*, Antonio GRILO 3, Rafael ROBINA RAMIREZ 4 1International University of La Rioja, Faculty of Business and Communication, Department of Business Organization, Marketing and Market Research, Av. de la Paz, 137, 26006 Logroño, Spain 2Rey Juan Carlos University, Faculty of Social Sciences and Law, Department of Business Economics, Paseo Artilleros s/n, Madrid 28032, Spain 3NOVA University Lisbon, Faculdade de Ciências e Tecnologia, Campus FCT/UNL, UNIDEMI, Monte da Caparica, 2829-519 Caparica, Portugal 4University of Extremadura, Faculty of Business, Finance and Tourism, Department of Business Management and Sociology, 10071 Caceres, Spain Received 9 June 2019; accepted 23 April 2020 Abstract. This article examines the main factors that affect creativity in startups and how these factors influence entrepreneurial initiative strategies. Fifty individuals from the Extremadura region, Spain, participated in an online questionnaire in 2018 and 2019. SmartPLS was used to create a model of the interactions between variables. The results obtained have important theoretical and practical implications as they add new findings to the current literature on the role played by different factors in the creativity processes used by startups. The model has a strong predictive power (R2= 42.7%). This work describes internal factors such as the improvement in intellectual and attitudinal skills for identifying business opportunities as a preliminary step to taking creative business decisions, as well as shaping the future by coordinating potential efforts and actions. Keywords: creativity, entrepreneurship, partial least squares structural equation modeling, startup business. Introduction The appearance of new technologies has created a business ecosystem which includes innovative projects that increase the amount of competition and added value, which are the main ways to obtain profitability in business initiatives (King & Levine, 1993; Venkataraman, 2019; Aldrich & Martinez, 2015). 388 P. Palos-Sanchez et al. How attitudes, vision and ability to capture opportunities affect startups’ business... An ecosystem of small technological companies which have their business strategies based on innovation has emerged in an environment of technological development (Yolanda & Syuraini, 2019) and are known as startups (Ben Chikha & Jarboui, 2017; Mas-Tur, Roig-Tierno, & Ribeiro Soriano, 2016). Creativity and innovation are the reasons for the success of their projects (Ven, Hudson, & Schroeder, 1984). In an ecosystem of startups and entrepreneurial projects which use the techniques of digital marketing and the main strategies of data analysis and associated technologies (Saura & Bennett, 2019). It is essential that the technological startups and entrepreneurial projects can detect opportunities and have a vision of the business sectors, which they are marketing to so that they can create successful projects (Almeida, Dokko, & Rosenkopf, 2003; Yunis, Tarhini, & Kassar, 2018). Startups and entrepreneurial projects with technological innovation are usually supported by grants that come from institutions such as the university, government institutions for innovation (Sulistyo & Siyamtinah, 2016), or start-up accelerators and incubators where business angels select and invest in creative innovation projects (Bennett, Pérez-Bustamante Yábar, & Saura, 2017). The themes and scopes of the business projects that startups detect and decide to develop are essential for the exponential development of the technology and projects (Lee, Hallak, & Sardeshmukh, 2016). Another important point for the success of the business model is the ability of the startup team to implement creative strategies. These teams must be multidisciplinary, creative and expert in strategy and innovation (Zapatero etal., 2018; Saura, Palos- Sanchez, & Grilo, 2019b). The leadership capacity and the vision of the startups, as well as the initiative to generate new business models, is what is known as “pivoting” in the world of startups. Therefore, being able to pivot is essential for these business models to be solid in the long term (Kazanjian, Drazin, & Glynn, 2002). Likewise, creativity is the ability to develop ideas that can be used to satisfy the requested needs and demands. Creativity in startups is important for making an impact on the audience and transmitting the innovation to the audience in an effective way (Welter etal., 2017; Endrik etal., 2019). The vision of a startup is the definition of the projected route to success for a startup or what it wants to become in the long term and is an important factor in the variable ecosystem of startups (Ven etal., 1984; Cooper & Folta, 2017). Initiative is also important in the world of startups as it determines the actions a company takes in a changing environment in which decisions must be taken on a daily basis to obtain a powerful project that can pivot and propose new strategies (Saura, Palos-Sanchez, & Correia, 2019a). The creativity of startups can be seen to be important for successful projects (Zahra & George, 2002; Hitt & Ireland, 2017). The aim of this research is to identify the main factors that affect creativity in innovative startups and entrepreneurial projects and how these can influence the strategies for the entrepreneurial initiative. This study used a methodological approach of structural Creativity Studies, 2020, 13(2): 387–405 389 equation analysis with partial least squares structural equation modeling (PLS-SEM) software. The results of this research increase the bibliography for this research gap about the creativity of innovative startups and entrepreneurial projects and the generation of opportunities and initiative. The results of this research can also be used by innovative startups to improve their projects and creativity, along with their attitude and opportunity detection abilities in the technology and innovation ecosystem. This investigation is structured in the following way. First, there is a review of the literature of the main research in this field. Second, the methodology and development of the hypotheses is explained. Next, the analysis of the results and discussion are presented and finally, the conclusions. 1. Literature review Research has been done into different aspects of the ecosystem of startups and entrepreneurial projects using innovation in the last decade (Hooi etal., 2016; Kiani Mavi & Amin Afshar, 2017). Saura etal. (2019b) continued the research presented by Farinha etal. (2017) and Aisyah, Musa, and Ramli (2017) and presented a methodological approach to the study of the main indicators that make a startup successful. References to creativity, innovation, equipment and technology are all included in that study. Robina-Ramírez, Fernández-Portillo, and Díaz-Casero (2019) analyzed indicators for environmental startups, which means, the innovation and creativity processes in a new model of environmental valuation for newly created companies. Mazzarol etal. (1998) defined the role and importance of creativity in companies as a factor that motivates the success of business projects. Helbert (2016) studied the influence of creativity in startups, but in periods of crisis, in order to understand whether lack of creativity can negatively influence the crisis. Bennett etal. (2017) investigated the influence that universities have on the creativity of startup and entrepreneurial projects that are carried out in this ecosystem, as well as measuring the social values and the creativity of the innovation in these types of projects. Almeida etal. (2003) studied the mechanisms that startups have to detect opportunities and what their capacity is to make decisions in terms of motivation, enthusiasm and attitude. Aldrich and Martinez (2015) looked into the reason why entrepreneurs are not more creative and studied the relationship between creativity and innovation in order to define the factors that affect this relationship. Chu etal. (2004) investigated the influence of attitude and discipline on the creativite strategies at startups. Ensley, Hmieleski, and Pearce (2006) studied the importance of leadership in startups and entrepreneurial projects in order to manage teams correctly. The study also looked into how leadership affects the innovation and creativity of the projects being worked on. Table1 shows other studies that have studied creativity in startups with the approach proposed in this research. 390 P. Palos-Sanchez et al. How attitudes, vision and ability to capture opportunities affect startups’ business... Table1. Similar studies of creativity and startups (source: created by authors) Authors Description Rutten (2014) Show the influence of creativity in the development of startup projects by performing a partial least squares structural equation modeling analysis. Duchesne, Kourti, and MacGregor (2002) Performs a statistical process control type analysis to measure the time taken in the process changing strategies of startups (pivoting) taking into account variables such as innovation and creativity. Howley and Malamis (2014) Develops a partial least squares path modeling to measure the influence of hidden metrics in the creation of startup strategies. Endrik etal. (2019) Study the factors that influence digital startup sustainability with a partial least squares structural equation modeling for the analysis of startups in Indonesia. Saura etal. (2019b) Develops an approach using data mining and Latent Dirichlet allocation model to analyse the issues that influence the success of startups taking into account motivation, technology and creativity. 2. Hypothesis development The following constructs were proposed to measure the influence of creativity variables in startups (see Figure 1). Attitude is the predisposition that startup teams have when facing new challenges. Vision consists of the perception that startups have when visualizing their long-term objectives in order to achieve them. Ability to identify opportunities refers to the ability of startups to identify and discover business opportunities that allow them to grow. Capture of opportunities refers to the implementation of the identified opportunities (DiPietro & Anoruo, 2006; Freeman & Engel, 2007; Audretsch & Belitski, 2013; Rutten, 2014; Endrik etal., 2019) Initiative measures the degree to which startups start new projects and execute new strategies demanded by the market (Rutten, 2014). Research by Audretsch and Belitski (2013) showed that attitude has an important influence on the creativity of entrepreneurial projects which use the theory of knowledge in their research. Ven, Hudson, and Schroeder (1984) stated that attitude, along with creativity in the development of new startups is of great importance for their success. These investigations and the link between attitude and creativity led to the following hypotheses: H1. The attitude of the startups’ teams influences the creativity of the startups’ strategies. Saura etal. (2019b) highlighted the importance of teams and their attitude and motivation for success when facing new challenges in a digital ecosystem. Reynolds (2001) also linked the attitude of startups with the vision and consolidation of their business projects after measuring the background of business startups. The following hypothesis was proposed using these investigations (Duchesne etal., 2002). H2. The teams’ attitude influences the vision for startup projects. Freeman and Engel (2007) linked the ability to identify opportunities for creativity with the development of innovation models in startups. Marlet and van Woerkens (2004) carried out a Creativity Studies, 2020, 13(2): 387–405 391 study to find the skills that accompany creativity in the identification of opportunities (Howley & Malamis, 2014). The following hypothesis was proposed from these investigations: H3. The ability to identify opportunities for startup teams influences the creativity of their strategies. Kuo and Gerber (2012) set out the principles of creativity in crowdfunding platforms startups, and identified the skills that startups need to identify opportunities in environments that satisfy the vision of the startup (Nambisan, 2017; Meyer etal., 2002). Endrik etal. (2019) looked at the sustainability of startups and studied the factors that help identify new business models and opportunities for this type of business. The following hypothesis was therefore proposed: H4. The ability of startup teams to identify opportunities influences the vision of startup projects. DiPietro and Anoruo (2006) studied how innovation and creativity influenced export performance. In their study, Creativity was found to have positive effects on the ability to detect opportunities. In addition, Montiel Campos etal. (2015) used a creative thinking style model to detect opportunities for startups and linked the influence of creativity to this decision making process (Endrik etal., 2019). The following hypothesis was therefore proposed: H5. The creativity of startup strategies influences the ability of startup teams to detect opportunities. Montiel Campos etal. (2015) used a design thinking model and discovered that the ability of entrepreneurs to identify opportunities is linked to the effectiveness of the initiative when creating new projects or opening new lines of products. Kuo and Gerber (2012) referred to entrepreneurship when talking about crowd funding startups that use creativity as a main tool in their business processes. The following hypothesis was proposed from this research: H6. The ability to identify startup opportunities influences the initiative to pivot or develop new strategies. Freeman and Engel (2017) found that the startup team’s vision of innovative projects helps it to face new opportunities and execute them correctly because of its capacity for innovation and creativity. The successful identification and development of new opportunities is important for the vision of new startup projects (Endrik etal., 2019). The following research hypothesis was then proposed: H7. The vision of startup projects influences the capture of new opportunities. Startup Attitude (SA) Ability to Identify Opportunities (AIO) Startup Opportunity (SO) Startup Lead (SL) Startup Creativity (SC) H1 Startup Vision (SV) H4 H2 H3 Figure 1. The proposed model (source: created by authors) 392 P. Palos-Sanchez et al. How attitudes, vision and ability to capture opportunities affect startups’ business... 3. Methodology An empirical study was used to test the hypotheses. This consisted of an electronically administered questionnaire for residents of the Extremadura region in Spain. The electronic survey was available on the www.diagnosticoemprende.com website of the regional government. The questionnaire is a tool that surveys and shows the results of strengths and weaknesses on a polar graph. 3.1. Data sample The questionnaires were offered to participants (n= 1547) who were selected with the help of the entrepreneur guidance and support services of the regional government. The participants had previously requested funds or technical support for a startup. A pretest with a sample of 46 individuals was used to validate the questionnaire and obtain comments on its structure, the order of the questions and the content in order to refine it. University students, technicians, professors and researchers of entrepreneurship at the university and Government de Extremadura were invited to take part in this pretest group. All incomplete questionnaires, those that contained systematic or inconsistent answers and any observations that did not meet the criteria suggested by Hair etal. (2017) were eliminated from the sample. These answers were not added to the final sample, but they did serve to modify the wording of some items. The questionnaire data was collected between January 2018 and February 2019. Table2 shows the profile of the members of the sample, where it can be seen that most of the respondents were women. The final sample was made up of 1547 people. The educational levels were: primary education 31.4% (485), secondary education 32.7% (506), university studies 34.7% (537) and special entrepreneurship training programs 1.2% (19). Another variable that was measured was the place of residence of the entrepreneur: 25.7% (397) came from cities with less than 75,000 inhabitants, 18.0% (279) from towns with 20 000–75 000 inhabitants, 21.1% (327) from villages of 5000–20 000 inhabitants and 35.2% (544) from places with less than 5000 inhabitants. More than 70% of the respondents are in the process of creating the company. That is to say, it is businesses that are starting up and are part of an innovative idea, generally associated with technological development. The rest have been in business for less than 3 years. Table2. Profile of respondents (n= 1547) (source: created by authors) Sexo Age Residence Woman Man <25 years 25 years ≤ x ≤45 years >45 years Region 47.30% 52.70% 16.20% 48.78% 36.02% Extremadura, Spain 3.2. Measuring instruments All the constructs were measured with a five-point Likert scale using indicators taken from the theoretical review, where 1= total disagreement and 5= total agreement. The ability to identify opportunities (AIO) construct was measured with three items, which were: AIO1– Creativity Studies, 2020, 13(2): 387–405 393 I value opportunities in social, cultural and economic terms, AIO2– I value the potential of an idea to create value and AIO3– I identify the most appropriate way to maximize my entrepreneurial idea. The startup attitude (SA) construct was measured with 4 items: SA1– I am confident in myself, SA2– I am aware of my needs and aspirations in the short, medium and long term, SA3– I know my individual and group strengths and weaknesses and, last, SA4– I believe in my ability to influence the course of events, despite uncertainty, setbacks and temporary failures. The startup vision (SV) construct was measured with 3 items: SV1– I am able to imagine the future, SV2– I am able to turn ideas into action and SV3– I am able to imagine future scenarios, which helps me coordinate efforts and actions. The startup creativity (SC) construct was measured with 3 items: SC1– I am able to work on several ideas and opportunities at the same time, SC2– I try innovative approaches, and SC3– I combine knowledge and resources to achieve results daily. The startup opportunity (SO) construct was also measured with 3 items: SO1– I identify and take advantage of opportunities to create value in my social, cultural and economic environment, SO2– I identify the needs and challenges that must be met, and SO3– I am capable of finding opportunities in my environment to create value. The most endogenous construct of the model was startup leadership (SL). This was measured with 3 items: SL1– I consider myself a person with entrepreneurial initiative, SL2– challenges do not worry me, and SL3– I am an independent worker when carrying out planned tasks. 3.3. Data analysis techniques The PLS technique was used to test the proposed model. This is an approach used to model structural equations with variance and SmartPLS 3.2.7 software (Ringle, Silva, & Bido, 2014). There are various reasons for this choice, such as, the constructs in the model are composite and therefore suitable for the application of PLS (Roldán & Sánchez-Franco, 2012). Also, this aim of this study is to identify the constructs that can help the reputation and image of the national brand (Hair, Ringle, & Sarstedt, 2011). All the constructs were modeled in Mode A. 4. Results 4.1. Measurement model The measurement model was used to evaluate all the constructs estimated as Mode A. The traditional measurements of internal consistency, reliability and validity were calculated for these constructs (Henseler, Ringle, & Sarstedt, 2016). As a general rule, a satisfactory value for reliability is obtained when the values of both the indicators and the dimensions exceed 0.7. In our case, all the indicators of the Mode A constructs exceed this critical value (Table3). In addition, the composite reliability was higher than 0.7 (Table3), thus meeting the requirements. 394 P. Palos-Sanchez et al. How attitudes, vision and ability to capture opportunities affect startups’ business... Table3. Results of the measurement model (source: created by authors) Construct/ Indicator Reliability Composite reliability Average variance extracted Ability to identify opportunities (AIO) 0.896 0.742 AIO1 I am confident in myself. 0.801 AIO2 I am aware of my needs and aspirations in the short, medium and long term. 0.809 AIO3 I know my individual and group strengths and weaknesses. 0.791 AIO4 I believe in my ability to influence the course of events, despite uncertainty, setbacks and temporary failures. 0.818 Startup creativity (SC) 0.875 0.701 SC1 I am able to work on several ideas and opportunities at the same time. 0.863 SC2 I try innovative approaches. 0.838 SC3 I combine knowledge and resources to achieve results daily. 0.810 Startup lead (SL) 0.857 0.669 SL1 I consider myself a person with entrepreneurial initiative. 0.866 SL2 Challenges do not worry me. 0.858 SL3 I am an independent worker when carrying out planned tasks. 0.722 Startup opportunity (SO) 0.903 0.756 SO1 I identify and take advantage of opportunities to create value in my social, cultural and economic environment. 0.879 SO2 I identify the needs and challenges that must be met. 0.868 SO3 I am capable of finding opportunities in my environment to create value. 0.863 Startup vision (SV) 0.878 0.706 SV1 I am able to imagine the future. 0.789 SV2 I am able to turn ideas into action. 0.844 SV3 I am able to imagine future scenarios, which helps me coordinate efforts and actions. 0.885 Creativity Studies, 2020, 13(2): 387–405 395 To demonstrate the convergent validity of the Mode A constructs, the average variance extracted (AVE) was calculated. In our model all constructs and dimensions satisfy this criterion since their AVE value exceeds the minimum level of 0.5 (Table3). Two methods were used to find the discriminant validity, which indicates that each construct differs from the other constructs. Firstly, the value of correlation squared for the construct must not exceed the value of the AVE (Fornell & Larcker, 1981). The Heterotrait- Monotrait Ratio of Correlations (HTMT) is another value which was checked (Henseler, Ringle, & Sarstedt, 2015). All the values in the matrix are below 0.85 (Kline, 2010), and the confidence intervals for HTMT do not reach the value of 1 (Henseler etal., 2015) so discriminant validity can be accepted (Table4). Table4. Measurement model: discriminant validity (source: created by authors) Fornell–Larcker Criterion Ability to identify opportunities (AIO) Startup attitude (SA) Startup creativity (SC) Startup lead (SL) Startup opportunity (SO) Startup vision (SV) AIO 0.861 SA 0.654 0.805 SC 0.753 0.638 0.837 SL 0.657 0.653 0.652 0.818 SO 0.753 0.674 0.770 0.653 0.870 SV 0.736 0.641 0.723 0.639 0.685 0.840 Heterotrait–Monotrait Ratio of Correlations Ability to identify opportunities (AIO) Startup attitude (SA) Startup creativity (SC) Startup lead (SL) Startup opportunity (SO) Startup vision (SV) AIO SA 0.790 SC 0.841 0.788 SL 0.818 0.815 0.830 SO 0.847 0.81 0.844 0.802 SV 0.845 0.786 0.840 0.808 0.831 In order to control the possible bias attributable to the measurement variable, the procedure recommended by Podsakoff etal. (2003) was applied. In addition, a complete collinearity test for variance inflation factor (VIF) was used in order to detect possible biases of Kock (2015). 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European Journal of Family Business, 8, 151–160. https://doi.org/10.24310/ejfbejfb.v8i2.5567 Creativity Studies, 2020, 13(2): 387–405 405 KAIP ĮSITIKINIMAI, POŽIŪRIS IR GEBĖJIMAS PASINAUDOTI GALIMYBĖMIS DARO ĮTAKĄ STARTUOLIŲ VERSLO KŪRYBIŠKUMUI Pedro PALOS-SANCHEZ, José Ramón SAURA, Antonio GRILO, Rafael ROBINA RAMIREZ Santrauka Šiame straipsnyje nagrinėjami pagrindiniai veiksniai, darantys įtaką startuolių kūrybiškumui ir prisidedantys prie antrepreneriškų iniciatyvinių strategijų. Penkiasdešimt žmonių iš Ekstramadūros regiono (Ispanija) 2018–2019m. dalyvavo internetinėje apklausoje. Kintamųjų sąveikos modeliui sukurti buvo naudojamasi SmartPLS kompiuterine programa. Gauti rezultatai yra svarbūs teoriškai ir praktiškai, nes naujausioje literatūroje jie papildė naujus atradimus apie tai, kokį vaidmenį įvairūs veiksniai atliko startuolių kūrybiškumo procesuose. Modeliui būdinga stipri prognostinė galia (R2= 42,7%). Šiame straipsnyje aprašomi vidiniai veiksniai, tokie kaip intelektiniai ir su požiūriu susiję gebėjimai, kuriuos pasitelkiant, verslo galimybės nustatomos kaip parengiamasis žingsnis prieš priimant kūrybinius verslo sprendimus, taip pat sudarant palankias sąlygas ateityje derinant galimas pastangas ir veiksmus. Reikšminiai žodžiai: kūrybiškumas, antreprenerystė, mažiausiųjų dalinių kvadratų struktūrinių lygčių modeliavimas, startuolių verslas.