Effect of knowledge resources on innovation and the mediating role of dynamic capabilities: case of medical tourism sector in Iran

Abstract

PurposeThis research is an empirical study that addresses whether knowledge resources impact on, or do not impact on, innovation development and if this impact is mediated by dynamic capabilities in the medical tourism sector in Mashhad city, Iran.Design/methodology/approachA quantitative research methodology was applied and questionnaires were used for data collection in this study. A total of 108 questionnaires were collected of which 102 questionnaires were valid. Data were analyzed using structural equation modelling technique.FindingsEmpirical evidence obtained from the study reveals that the dynamic capability of learning plays a significant role in transforming knowledge resources into innovation in the medical tourism sector. The mediating role of coordinating capability in the relationship between explicit and tacit knowledge and innovation is considerable and it influences human capital, as well. Sensing capability also exhibits some degree of a mediating role; however, integrating capability is not influential and its role in transforming explicit knowledge to innovation is rejected.Originality/valueMost studies on innovation in medical tourism focused on market and its typology, and neglected the role of knowledge resources and dynamic capabilities. The current study bridges this gap and thus contributes to the scientific literature.

Green Innovation Adoption in Turkish and Iranian SMEs: The Effect of Dynamic Capabilities and the Mediating Role of Absorptive Capacity

“…This evidence contradicts with some earlier findings (Huang & Li, 2017;Qiu et al, 2020;Singh et al, 2019;Yousaf, 2021). Edgar et al (2024) found that DC of learning is influential in transforming knowledge resources into innovation for Iranian firms. However, Wilden et al (2013) and Zhou et al (2019) discuss DC have different effects.…”

“…Ar, 2012;Barforoush et al, 2021;Dangelico et al, 2017;Gürlek & Tuna, 2018;Jabarzadeh et al, 2022;Şengüllendi et al, 2023;Yousaf, 2021;Yurdakul & Kazan, 2023) and partial least squares-structural equation modelling (e.g. Aboelmaged & Hashem, 2019;Albort-Morant et al, 2016 ;Ahmad et al, 2024;Awan et al, 2021;Bhatia & Jakhar, 2021;Edgar et al, 2024) are the most frequently-used techniques in the GI adoption or performance literature. Apart from those techniques, many earlier studies have also utilized from regression analysis (Jahanshahi et al, 2020;Leenders & Chandra, 2013;Qiu et al, 2020;Sezen & Yıldız Çankaya, 2013;Tepe Küçükoğlu & Pınar, 2015;Zhang & Zhu, 2019), partial least squares-path modelling approach (Albort Morant et al, 2018b;Singh et al, 2022), multi-criteria decision-making (Fahad et al, 2022;Musaad et al, 2020), hierarchical linear modelling (Xue et al, 2019;Zhang et al, 2020), confirmatory factor analysis (Lin & Chen, 2017) to analyze GI adoption or performance.…”

Dynamic capabilities and SMEs competitiveness: the moderating effect of market turbulence

“…Because tourism was among the business sectors most negatively affected by the COVID-19 pandemic (Senbeto and Hon, 2020), TSMEs were chosen for this investigation. Also, most DC studies dealt with the production sector, with few focused on service companies such as those in tourism (Edgar et al , 2022). Wided (2022) argued that DCs were vital for achieving sustainable tourism.…”

The coupling and coordination relationship of the digital economy and tourism industry from the perspective of industrial integration

“…Moreover, industrial integration has become a new driving force for promoting the evolution of tourism industry models and formats (Lu, 2011). Research on the integration of the tourism industry has gradually refined and matured, and the content has become more and more extensive, such as the integration of tourism and the cultural industry (Bordoni, 2011), sports industry (Zhu, 2022) and medical industry (Edgar et al, 2022;Parekh et al, 2021). Due to the different integration parties, the integration development models also vary.…”