62 research outputs found

    How past decisions affect future behavior on ecoinnovation: An empirical study

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    This is the peer reviewed version of the following article: Peiró Signes, Angel, Segarra-Oña, Marival. (2018). How past decisions affect future behavior on ecoinnovation: An empirical study.Business Strategy and the Environment, 27, 8, 1233-1244. DOI: 10.1002/bse.2071, which has been published in final form at https://doi.org/10.1002/bse.2071. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving[EN] The environment is increasingly gaining importance for citizens and society and, therefore, for consumers. Eco-innovation is a direct path for reducing the impact of production while providing companies with a source of competitive advantage. The automotive industry and its supply chain have a great impact on the environment, but no research has been developed on how the orientation toward the environment is evolving for the automotive industry and how future performance may be affected by current decisions. The aim of this paper is to bridge this gap by analyzing the eco-innovative dynamism of the automobile industry. To do this, we use a panel analysis to see the point at which past behavior influences future decisions. The partial least square method is used to analyze the eco-innovative dynamism of the automobile industry. We analyze a data set based on 159 responses of Spanish companies that belong to the automobile sector. Results show that environmental orientation drivers do not evolve over a short period while in the longer term there is an evolution. We prove that carryover effects have a great impact on the future behavior of the firms, showing that the evolution of organizations' environmental behavior is a long-range consideration. Managerial implications arise from this paper's conclusions, as the decision-making process is clarified.Peiró Signes, A.; Segarra-Oña, M. (2018). How past decisions affect future behavior on ecoinnovation: An empirical study. Business Strategy and the Environment. 27(8):1233-1244. https://doi.org/10.1002/bse.2071S1233124427

    The Effect of Green Certificates on the Purchasing Decisions of Online Customers in Green Hotels: A Case Study from Saudi Arabia

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    [EN] Customers are becoming more concerned about the use of green practices in the hotel industry. Managers are therefore starting to recognise the significance of green practices for clients' purchasing decisions and levels of satisfaction. This study aims to investigate how customers' decisions to book green hotels online and make purchases are impacted by green certificates. Two variables, namely the intentions to return and to pay a premium price, are used to measure customer satisfaction and purchasing behaviour towards green hotels. SmartPLS has been employed to analyse data gathered from 161 individuals from two hotels in Saudi Arabia. The results suggest that green certifications, environmental considerations, and green brand perception have a significant impact on online customers' satisfaction and purchase choices in the hotel sector. This paper provides a comprehensive framework that illustrates the connection between hotels' aspirations towards environmental concerns and customers' willingness to revisit and pay a premium price.This research was supported by two conference grants from Christian Heritage College.Qubbaj, AI.; Peiró Signes, A.; Najjar, M. (2023). The Effect of Green Certificates on the Purchasing Decisions of Online Customers in Green Hotels: A Case Study from Saudi Arabia. Sustainability. 15(7):1-15. https://doi.org/10.3390/su1507589211515

    Building a Theoretical Framework for Corporate Sustainability

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    [EN] Literature about sustainability and sustainable businesses has become a large field of study during the last years. This field is growing so fast that there are sub-areas or bodies of literature within the sustainability which scopes with clear boundaries between each other. This has caused the apparition of several methodologies and tools for turning traditional companies into sustainable business models. This paper aims to develop the descriptive stage of the theory building process through a careful review of literature to create the first phase of a theory about corporate sustainability. It provides the following classification of concepts retrieved from the observation of the state of art: holistic sustainability, sustainable business models, sustainable methodologies, sustainable operations, and sustainability-oriented innovation. In addition, it seeks to establish relationships between the sustainable concepts and the expected outcomes that their implementation can generate among companies and organizations. Finally, it gives an overview of possibilities for managers that want to embed sustainability in their firms and clear paths of research for keeping the building of the theory about corporate sustainability as a process of constant iteration and improvement.This research was funded by the Ministry of Science and Innovation, project number: PID2019-105497GB-100.Sanchez-Planelles, J.; Segarra-Oña, M.; Peiró Signes, A. (2021). Building a Theoretical Framework for Corporate Sustainability. Sustainability. 13(1):1-21. https://doi.org/10.3390/su13010273S12113

    Can a country's environmental sustainability exert influence on its economic and financial situation? The relationship between environmental performance indicators and country risk

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    [EN] Due to international events such as the declaration of Sustainable Development Goals, countries have started to develop their national strategies for effective implementation of the 2030 Agenda based on those targets. This study aimed to analyse the existing relationship between the environmental proactiveness and sustainability of countries and their associated Country Risk Scores. For this purpose, two main indicators were considered: (a) the Environmental Performance Index, as a measure of a country's environmental sustainability pro-activeness, and (b) the Country Risk Score, which represents a country's economic, political, and financial situation. Data for 163 countries were used to test whether the Environmental Performance Index is related to the Country Risk Score while controlling for country groupings (memberships and/or alliances). This analysis was complemented by a regression approach using fuzzy-set qualitative comparative analysis to identify the combination of con-ditions leading to a high or low Country Risk Score. The results showed that the Environmental Performance Index is a good predictor of the Country Risk Score. In particular, the Environmental Health component of the Environmental Performance Index emerged as a better fit. However, the complementary analysis uncovered the important role of Ecosystem Vitality. Furthermore, the analysis confirmed the moderating effect of the country groupings. Overall, the Environmental Performance Index scores correlate with Country Risk Scores. The Environmental Performance Index reflects good governance practices, which are related to those evaluated by the Country Risk Score.This publication is part of the Program for Assessing and Resources sets R+D+i VLC/CAMPUS and has been funded by the Ministry of Education, Culture and Sports as part of the Campus of International Excellence Program. The authors would like to thank the Universitat Politecnica de Valencia (UPV) for the support through the grant number: PAID-06-14 to the project SP20140647 'Identification of moderating factors in the eco-innovative orientation of society. A social innovation approach'.Peiró Signes, A.; Cervelló Royo, RE.; Segarra-Oña, M. (2022). Can a country's environmental sustainability exert influence on its economic and financial situation? The relationship between environmental performance indicators and country risk. Journal of Cleaner Production. 375:1-10. https://doi.org/10.1016/j.jclepro.2022.13412111037

    Impact of National Cultures on Automotive Sector After Sales Services Perception

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    [EN] This article clarifies the impact of national culture in the after sales service in the automotive sector.. Introduction and objectives: After-sales services have become paramount in the automobile industry. How-ever, they are not sufficiently researched, particularly in emerging markets. Here an academic gap exists be-cause, within the automotive research literature, culture is a widely neglected issue. Thus no explicit knowledge can be applied regarding emerging markets service demand behaviour, which might be a crucial point, as some of these countries culture is different to the western culture. Methods: The research is based in a survey carried out among Chinese premium brand automotive customers. Results: It shows which individual level values are causal and positively contribute to the perception of service quality and loyalty behaviour by customers. Con-clusion: The article providing a guideline how the entire process chain of after-sales services could be re-searched and applies successfully the individual level value theory by Schwartz. Implications and research limitation: Brand loyalty is well explained by perceived service quality significantly leads to after-sales service satisfaction, which itself is a strong predictor of workshop loyalty. Moreover, workshop loyal customers are likewise significantly brand loyal, Finally, the influence of culture is empirically verified with the one exception of after-sales service satisfaction.Albors Garrigós, J.; Frass, A.; Schoeneberg, KP.; Peiró Signes, A. (2017). Impact of National Cultures on Automotive Sector After Sales Services Perception. Management Journal of Sustainable Business and Management Solutions in Emerging Economies. 22(2):13-27. doi:10.7595/management.fon.2017.0014S132722

    Determinantes de la eco-innovacion en el sector servicios

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    [EN] The objective of this paper is to determine, empirically, the determinants of service firms’ environmental orientation (firm environmental responsiveness and environmental performance) while innovating. We analyze 3013 Spanish service firms using multivariate analysis with data retrieved from PITEC Database (Spanish Technological Panel). Results show that environmentally oriented service firms are characterized by product and process orientation. Furthermore, results show that service eco-oriented firms are those that have been more innovative and that rely more on market information sources for the innovation process.[ES] El objetivo de este trabajo es determinar, empíricamente, los determinantes de la orientación medioambiental de las empresas de servicios (responsabilidad medioambiental de las empresas y comportamiento medioambiental) cuando innovan. Hemos analizado 3013 empresas de servicios españolas mediante análisis multivariante con datos obtenidos de la base de datos de PITEC (Panel de innovación tecnológica). Los resultados muestran que las empresas de servicios medioambientalmente orientadas se caracterizan por la orientación hacia productos y procesos. Además, los resultados muestran que las empresas de servicios eco-orientadas son aquellas que han sido más innovadoras y que se basan en fuentes de información de mercado cuando innovan.The authors would like to thank the Universitat Politècnica de València for its research funding to the project (PAID-06-2011-1879) and the Spanish Economy and Competitiveness Ministry for its financial support through the research project (EC02011- 27369).Segarra Oña, MDV.; Peiró Signes, A. (2013). Eco-innovation determinants in service industries. Dirección y Organización. 50:5-16. http://hdl.handle.net/10251/59672S5165

    Anxiety towards Statistics and Its Relationship with Students' Attitudes and Learning Approach

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    [EN] Many university students have difficulties when facing statistics related tasks, leading to an increase in their levels of anxiety and poor performance. Researchers have identified negative attitudes towards statistics, which have been shaped through students' secondary education experience, as a major driver for their failure. In this study we want to uncover the causal recipes of attitudes leading to high and low levels of anxiety in secondary education students, and the role that the learning approach plays in these relationships. We used fuzzy sets comparative qualitative analysis (fsQCA) in a sample of 325 students surveyed on the multifactorial scale of attitudes toward statistics (MSATS) and the revised two factor study process questionnaire (R-SPQ-2F). The results indicate that, respectively, a high or a low level of self-confidence is the most important and a sufficient condition by itself for achieving a low or a high level of anxiety, while the learning approaches and other attitudes are only present in other causal combinations that represent a small number of cases.Peiró Signes, A.; Trull, O.; Segarra-Oña, M.; García-Díaz, JC. (2021). Anxiety towards Statistics and Its Relationship with Students' Attitudes and Learning Approach. Behavioral Sciences. 11(3):1-13. https://doi.org/10.3390/bs11030032S11311

    Attitudes towards statistics in secondary education: Findings from fsQCA

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    [EN] Students report a high degree of anxiety and reduced self-confidence when facing statistical subjects, especially in secondary education. This anxiety turns into poor academic performance. Most studies have used linear models for studying the interrelation between different attitudes and proving their impact on performance or related variables. This study uses a different approach to explain and better understand the causal patterns of factors stimulating lower levels of anxiety in students when facing statistics in secondary education. We employed the Multi-factorial Scale of Attitudes Toward Statistics (MSATS) and fuzzy-set qualitative comparative analysis (fsQCA) on a sample of 95 secondary school students in Spain. We identified the recipes or causal combination of factors, leading to low and high levels of anxiety. The results indicate that self-confidence and motivation are important factors in these recipes, but there is no single necessary condition that ensures lower levels of anxiety.Peiró Signes, A.; Trull, Ó.; Segarra-Oña, M.; García-Díaz, JC. (2020). Attitudes towards statistics in secondary education: Findings from fsQCA. Mathematics. 8(5):1-17. https://doi.org/10.3390/math8050804S11785Gal, I., & Ginsburg, L. (1994). The Role of Beliefs and Attitudes in Learning Statistics: Towards an Assessment Framework. Journal of Statistics Education, 2(2). doi:10.1080/10691898.1994.11910471Cashin, S. E., & Elmore, P. B. (2005). The Survey of Attitudes Toward Statistics Scale: A Construct Validity Study. Educational and Psychological Measurement, 65(3), 509-524. doi:10.1177/0013164404272488Garfield, J., & Ben-Zvi, D. (2007). How Students Learn Statistics Revisited: A Current Review of Research on Teaching and Learning Statistics. International Statistical Review, 75(3), 372-396. doi:10.1111/j.1751-5823.2007.00029.xChiesi, F., & Primi, C. (2009). Assessing statistics attitudes among college students: Psychometric properties of the Italian version of the Survey of Attitudes toward Statistics (SATS). Learning and Individual Differences, 19(2), 309-313. doi:10.1016/j.lindif.2008.10.008Beins, B. (1985). Teaching the Relevance of Statistics through Consumer-Oriented Research. Teaching of Psychology, 12(3), 168-169. doi:10.1207/s15328023top1203_16Rojo Robas, V., Madariaga, J. M., & Villarroel, J. D. (2020). Secondary Education Students’ Beliefs about Mathematics and Their Repercussions on Motivation. Mathematics, 8(3), 368. doi:10.3390/math8030368Roberts, D. M., & Bilderback, E. W. (1980). Reliability and Validity of a Statistics Attitude Survey. Educational and Psychological Measurement, 40(1), 235-238. doi:10.1177/001316448004000138Wise, S. L. (1985). The Development and Validation of a Scale Measuring Attitudes toward Statistics. Educational and Psychological Measurement, 45(2), 401-405. doi:10.1177/001316448504500226Schau, C., Stevens, J., Dauphinee, T. L., & Vecchio, A. D. (1995). The Development and Validation of the Survey of Antitudes toward Statistics. Educational and Psychological Measurement, 55(5), 868-875. doi:10.1177/0013164495055005022Roberts, D. M., & Saxe, J. E. (1982). Validity of a Statistics Attitude Survey: A Follow-Up Study. Educational and Psychological Measurement, 42(3), 907-912. doi:10.1177/001316448204200326ZEIDNER, M. (1991). STATISTICS AND MATHEMATICS ANXIETY IN SOCIAL SCIENCE STUDENTS: SOME INTERESTING PARALLELS. British Journal of Educational Psychology, 61(3), 319-328. doi:10.1111/j.2044-8279.1991.tb00989.xBaloğlu, M. (2003). Individual differences in statistics anxiety among college students. Personality and Individual Differences, 34(5), 855-865. doi:10.1016/s0191-8869(02)00076-4Schram, C. M. (1996). A Meta-Analysis of Gender Differences in Applied Statistics Achievement. Journal of Educational and Behavioral Statistics, 21(1), 55-70. doi:10.3102/10769986021001055Clute, P. S. (1984). Mathematics Anxiety, Instructional Method, and Achievement in a Survey Course in College Mathematics. Journal for Research in Mathematics Education, 15(1), 50. doi:10.2307/748987Froelich, A. G., Stephenson, W. R., & Duckworth, W. M. (2008). Assessment of Materials for Engaging Students in Statistical Discovery. Journal of Statistics Education, 16(2). doi:10.1080/10691898.2008.11889561Onwuegbuzie, A. J., & Daley, C. E. (1999). Perfectionism and statistics anxiety. Personality and Individual Differences, 26(6), 1089-1102. doi:10.1016/s0191-8869(98)00214-1Benson, J. (1989). Structural Components of Statistical Test Anxiety in Adults. The Journal of Experimental Education, 57(3), 247-261. doi:10.1080/00220973.1989.10806509CARMONA, J. (2005). MATHEMATICAL BACKGROUND AND ATTITUDES TOWARD STATISTICS IN A SAMPLE OF SPANISH COLLEGE STUDENTS. Psychological Reports, 97(5), 53. doi:10.2466/pr0.97.5.53-62Macher, D., Paechter, M., Papousek, I., & Ruggeri, K. (2011). Statistics anxiety, trait anxiety, learning behavior, and academic performance. European Journal of Psychology of Education, 27(4), 483-498. doi:10.1007/s10212-011-0090-5Musch, J., & Broder, A. (1999). Test anxiety versus academic skills: A comparison of two alternative models for predicting performance in a statistics exam. British Journal of Educational Psychology, 69(1), 105-116. doi:10.1348/000709999157608Onwuegbuzie, A. J., & Seaman, M. A. (1995). The Effect of Time Constraints and Statistics Test Anxiety on Test Performance in a Statistics Course. The Journal of Experimental Education, 63(2), 115-124. doi:10.1080/00220973.1995.9943816Tremblay, P. F., Gardner, R. C., & Heipel, G. (2000). A model of the relationships among measures of affect, aptitude, and performance in introductory statistics. Canadian Journal of Behavioural Science / Revue canadienne des sciences du comportement, 32(1), 40-48. doi:10.1037/h0087099Hardy, L., & Hagtvet, K. A. (1996). Anxiety and performance: Measurement and modelling issues. Anxiety, Stress & Coping, 9(1), v-viii. doi:10.1080/10615809608249388King, N. J., Ollendick, T. H., & Gullone, E. (1991). Test anxiety in children and adolescents. Australian Psychologist, 26(1), 25-32. doi:10.1080/00050069108258829Seipp, B. (1991). Anxiety and academic performance: A meta-analysis of findings. Anxiety Research, 4(1), 27-41. doi:10.1080/08917779108248762Sesé, A., Jiménez, R., Montaño, J. J., & Palmer, A. (2015). Can Attitudes toward Statistics and Statistics Anxiety Explain Students’ Performance? // ¿Pueden las actitudes hacia la estadística y la ansiedad estadística explicar el rendimiento de los estudiantes? Revista de Psicodidactica / Journal of Psychodidactics, 20(2), 285-304. doi:10.1387/revpsicodidact.13080Mondéjar-Jiménez, J., & Vargas-Vargas, M. (2010). Determinant factors of attitude towards quantitative subjects: Differences between sexes. Teaching and Teacher Education, 26(3), 688-693. doi:10.1016/j.tate.2009.10.004Nasser, F. M. (2004). Structural Model of the Effects of Cognitive and Affective Factors on the Achievement of Arabic-Speaking Pre-service Teachers in Introductory Statistics. Journal of Statistics Education, 12(1). doi:10.1080/10691898.2004.11910717Onwuegbuzie, A. J. (2003). Modeling Statistics Achievement among Graduate Students. Educational and Psychological Measurement, 63(6), 1020-1038. doi:10.1177/0013164402250989Lalonde, R. N., & Gardner, R. C. (1993). Statistics as a second language? A model for predicting performance in psychology students. Canadian Journal of Behavioural Science/Revue canadienne des sciences du comportement, 25(1), 108-125. doi:10.1037/h0078792Onwuegbuzie, A. J. (2000). Statistics Anxiety and the Role of Self-Perceptions. The Journal of Educational Research, 93(5), 323-330. doi:10.1080/00220670009598724Katz, B. M., & Tomazic, T. J. (1988). Changing Students’ Attitudes toward Statistics through a Nonquantitative Approach. Psychological Reports, 62(2), 658-658. doi:10.2466/pr0.1988.62.2.658Vanhoof, S., Castro Sotos, A. E., Onghena, P., Verschaffel, L., Van Dooren, W., & Van den Noortgate, W. (2006). Attitudes Toward Statistics and Their Relationship with Short- and Long-Term Exam Results. Journal of Statistics Education, 14(3). doi:10.1080/10691898.2006.11910588Bandalos, D. L., Finney, S. J., & Geske, J. A. (2003). A model of statistics performance based on achievement goal theory. Journal of Educational Psychology, 95(3), 604-616. doi:10.1037/0022-0663.95.3.604Bandalos, D. L., Yates, K., & Thorndike-Christ, T. (1995). Effects of math self-concept, perceived self-efficacy, and attributions for failure and success on test anxiety. Journal of Educational Psychology, 87(4), 611-623. doi:10.1037/0022-0663.87.4.611Schutz, P. A., Drogosz, L. M., White, V. E., & Distefano, C. (1998). Prior knowledge, attitude, and strategy use in an introduction to statistics course. Learning and Individual Differences, 10(4), 291-308. doi:10.1016/s1041-6080(99)80124-1Usher, E. L., & Pajares, F. (2008). Sources of Self-Efficacy in School: Critical Review of the Literature and Future Directions. Review of Educational Research, 78(4), 751-796. doi:10.3102/0034654308321456Comas, C., Martins, J. A., Nascimento, M. M., & Estrada, A. (2017). Estudio de las Actitudes hacia la Estadística en Estudiantes de Psicología. Bolema: Boletim de Educação Matemática, 31(57), 479-496. doi:10.1590/1980-4415v31n57a23Walsh, J. J., & Ugumba-Agwunobi, G. (2002). Individual differences in statistics anxiety: the roles of perfectionism, procrastination and trait anxiety. Personality and Individual Differences, 33(2), 239-251. doi:10.1016/s0191-8869(01)00148-9Ribes Giner, G., Perelló Marín, M. R., & Pantoja Díaz, O. (2017). Revisión sistemática de literatura de las variables clave del proceso de co-creación en las instituciones de educación superior. Literature review of the key variables of the co-creation process in higher education institutions. TEC Empresarial, 11(3), 41. doi:10.18845/te.v11i3.3365Müller-Merbach, H. (2008). Knowledge management: a program for education and leadership. Knowledge Management Research & Practice, 6(4), 350-356. doi:10.1057/kmrp.2008.25Carnell, L. J. (2008). The Effect of a Student-Designed Data Collection Project on Attitudes Toward Statistics. Journal of Statistics Education, 16(1). doi:10.1080/10691898.2008.11889551Slootmaeckers, K., Kerremans, B., & Adriaensen, J. (2013). Too Afraid to Learn: Attitudes towards Statistics as a Barrier to Learning Statistics and to Acquiring Quantitative Skills. Politics, 34(2), 191-200. doi:10.1111/1467-9256.12042Elmore, P. B., & Vasu, E. S. (1986). A Model of Statistics Achievement Using Spatial Ability, Feminist Attitudes and Mathematics-Related Variables as Predictors. Educational and Psychological Measurement, 46(1), 215-222. doi:10.1177/0013164486461025Fiss, P. C. (2011). Building Better Causal Theories: A Fuzzy Set Approach to Typologies in Organization Research. Academy of Management Journal, 54(2), 393-420. doi:10.5465/amj.2011.60263120Fiss, P. C. (2007). A set-theoretic approach to organizational configurations. Academy of Management Review, 32(4), 1180-1198. doi:10.5465/amr.2007.26586092Braumoeller, B. F. (2004). Hypothesis Testing and Multiplicative Interaction Terms. International Organization, 58(04). doi:10.1017/s0020818304040251Rihoux, B. (2006). Qualitative Comparative Analysis (QCA) and Related Systematic Comparative Methods. International Sociology, 21(5), 679-706. doi:10.1177/0268580906067836Woodside, A. G. (2013). Moving beyond multiple regression analysis to algorithms: Calling for adoption of a paradigm shift from symmetric to asymmetric thinking in data analysis and crafting theory. Journal of Business Research, 66(4), 463-472. doi:10.1016/j.jbusres.2012.12.021Liu, Y., Mezei, J., Kostakos, V., & Li, H. (2015). Applying configurational analysis to IS behavioural research: a methodological alternative for modelling combinatorial complexities. Information Systems Journal, 27(1), 59-89. doi:10.1111/isj.12094Betti, G., D’Agostino, A., & Neri, L. (2010). Educational Mismatch of Graduates: a Multidimensional and Fuzzy Indicator. Social Indicators Research, 103(3), 465-480. doi:10.1007/s11205-010-9712-6Tho, N. D., & Trang, N. T. M. (2015). Can knowledge be transferred from business schools to business organizations through in-service training students? SEM and fsQCA findings. Journal of Business Research, 68(6), 1332-1340. doi:10.1016/j.jbusres.2014.12.003Palacios-Marqués, D., Roig-Dobón, S., & Comeig, I. (2016). Background factors to innovation performance: results of an empirical study using fsQCA methodology. Quality & Quantity, 51(5), 1939-1953. doi:10.1007/s11135-016-0414-2Ordanini, A., Parasuraman, A., & Rubera, G. (2013). When the Recipe Is More Important Than the Ingredients. Journal of Service Research, 17(2), 134-149. doi:10.1177/1094670513513337Pappas, I. O., Kourouthanassis, P. E., Giannakos, M. N., & Chrissikopoulos, V. (2016). Explaining online shopping behavior with fsQCA: The role of cognitive and affective perceptions. Journal of Business Research, 69(2), 794-803. doi:10.1016/j.jbusres.2015.07.010Dul, J. (2016). Identifying single necessary conditions with NCA and fsQCA. Journal of Business Research, 69(4), 1516-1523. doi:10.1016/j.jbusres.2015.10.134Beynon, M. J., Jones, P., & Pickernell, D. (2016). Country-based comparison analysis using fsQCA investigating entrepreneurial attitudes and activity. Journal of Business Research, 69(4), 1271-1276. doi:10.1016/j.jbusres.2015.10.091Schneider, C. Q., & Wagemann, C. (2010). Standards of Good Practice in Qualitative Comparative Analysis (QCA) and Fuzzy-Sets. Comparative Sociology, 9(3), 397-418. doi:10.1163/156913210x12493538729793Ragin, C. C. (2006). Set Relations in Social Research: Evaluating Their Consistency and Coverage. Political Analysis, 14(3), 291-310. doi:10.1093/pan/mpj019Harlow, L. L., Burkholder, G. J., & Morrow, J. A. (2002). Evaluating Attitudes, Skill, and Performance in a Learning-Enhanced Quantitative Methods Course: A Structural Modeling Approach. Structural Equation Modeling: A Multidisciplinary Journal, 9(3), 413-430. doi:10.1207/s15328007sem0903_

    STEAM education at Master level

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    [EN] This work presents the Innovation and Improvement Learning Project ¿Applying STEAM strategies in the Social Sciences and Arts areas by means of a Service-learning methodology¿ that aims to facilitate the acquisition of the Science, Technology, Engineering, Arts and Maths competences of Master students in the Universitat Politécnica de València (UPV) by means of a service-learning focus. An interdisciplinary group of seven lecturers work in an own model that latter could be also applied to other Master and Bachelor Programs. By now, we have developed a competence sheet for each STEAM competence that could be applied in any subject that would like to work on it. To achieve these competences by a holistic approach, we also relate them to the UPV transversal competences and to the United Nations Sustainable Development Goals. The final objective is that any program could cover all the STEAM competences to add value to the students¿ learning. The first results show that, putting all these concepts together, we compel the students to propose creative solutions that could help organizations as well as individuals.This work has been developed within the project ¿Applying STEAM strategies in the Social Sciences and Arts areas by means of a Service-learning methodology¿, conducted by Professor María de Miguel Molina, and with the support of the Universitat Politécnica de València (Science Education Institute, ICE).De-Miguel-Molina, M.; Catalá-Pérez, D.; Peiró Signes, A.; Segarra-Oña, M. (2020). STEAM education at Master level. Iated. 1260-1264. https://doi.org/10.21125/inted.2020.04281260126

    Why and how hotel groups in luxury segments give back to their communities

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    This is the peer reviewed version of the following article: de‐Miguel‐Molina, B, de‐Miguel‐Molina, M, Segarra‐Oña, M, Peiró‐Signes, A. Why and how hotel groups in luxury segments give back to their communities. Int J Tourism Res. 2018; 20: 100‐ 114. https://doi.org/10.1002/jtr.2166, which has been published in final form at http://doi.org/10.1002/jtr.2166. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.[EN] The paper analyses why and how hotel groups become involved in their communities through philanthropic activities. The analysis focuses on hotel groups with brands in the luxury, upper upscale, and upscale segments. The qualitative information disclosed in reports and websites by 243 hotel brands was studied to answer questions about who is involved, how they participate, and who they target. The study then focused on the 130 hotel groups owning these brands, and a qualitative comparative analysis was used to explain the combination of causal conditions explaining why hotel groups participate in their communities. The causal conditions in the analysis included the participation of different stakeholders, the characteristics of the hotel groups, and the culture of the countries. Results indicate that there is a trade¿off between customer and employee participation in philanthropy, that customer involvement requires the presence of luxury brands, and that the culture of the countries (religion and altruism) stimulates the philanthropic behaviour of hotel groups.De-Miguel-Molina, B.; De-Miguel-Molina, M.; Segarra-Oña, M.; Peiró Signes, A. (2018). Why and how hotel groups in luxury segments give back to their communities. International Journal of Tourism Research. 20(1):100-114. https://doi.org/10.1002/jtr.216610011420
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