International Journal of Science Annals, Vol. 7, No. 1, 2024 рrint ISSN: 2617-2682; online ISSN: 2707-3637; DOI:10.26697/ijsa SOCIAL AND BEHAVIORAL SCIENCES. Health Care Sciences ORIGINAL RESEARCH Conceptualizing a Model for the Use of Software as a Service to Improve the Dynamic Capabilities of Small and Medium Enterprises in Healthcare Sector Authors’ Contribution: A – Study design; Makelana P.1 ABCDEFG , Kekwaletswe R.2 ABCDEFG , B – Data collection; Segooa M. A.1 ABCDEFG C – Statistical analysis; 1 Tshwane University of Technology, South Africa D – Data interpretation; 2 University of Johannesburg, South Africa E – Manuscript preparation; F – Literature search; Received: 31.05.2024; Accepted: 22.06.2024; Published: 30.06.2024 G – Funds collection Abstract Background and To remain competitive in today’s digital society, Small and Medium Enterprises Aim of Study: (SMEs) in the healthcare sector need to consider effective ways to improve their dynamic capabilities (DCs) using Software as a Service (SaaS). SaaS and DCs are current key issues in both academia and practice. The aim of the study: to develop the conceptual model for the use of SaaS to improve the DCs of healthcare SMEs in South Africa. Material and Methods: The study employed Task-Technology Fit (TTF) and Fit Viability Model (FVM) as a lens to develop a model for the use of SaaS to improve the DCs of healthcare SMEs. To achieve the aim of the study, a deductive approach was followed. The study population was healthcare SMEs, in South Africa. The sampling frame was 384 randomly selected SMEs, in a self-administered survey. Results: The study results show that customer service (β=0.125, p<0.05), sharing information (β=0.132, p<0.05), internet access (β=0.057, p<0.05), data security (β=0.022, p<0.05), top management support (β=0.427, p<0.05), competitive pressure (β=0.178, p<0.05), viability (β=0.325, p<0.05) and task-technology fit (β=0.032, p<0.05) are highly significant on the use of SaaS to improve the DCs of healthcare SMEs. While finance (β=0.235, p>0.05) and infrastructure (β=0.052, p>0.05) were found to be less significant. Conclusions: The conceptual model was developed to identify and explain the factors influencing the use of SaaS to improve the DCs of healthcare enterprises. This model is based on TTF, FVM and external constructs (organisational and environmental characteristics) that are key to improving the DC of South African healthcare SMEs. Keywords: dynamic capabilities, fit viability model, software as a service, small and medium enterprises, healthcare sector, South Africa Copyright: © 2024 Makelana P., Kekwaletswe R., Segooa M. A. Published by Archives of International Journal of Science Annals DOI: https://doi.org/10.26697/ijsa.2024.1.5 Conflict of interests: The authors declare that there is no conflict of interests Peer review: Double-blind review Source of support: This research did not receive any outside funding or support Information about Makelana Penuel (Corresponding Author) – https://orcid.org/0000-0003-0986- the authors: 1117; Penuel.kman@gmail.com; Doctor of Computing, Lecturer, Department of Informatics, Tshwane University of Technology, Pretoria, South Africa. Kekwaletswe Ray – https://orcid.org/0000-0002-3455-3127; Professor, School of Management, University of Johannesburg, Johannesburg, South Africa. Segooa Mmmatshuene Anna – https://orcid.org/0000-0002-4190-8256; Doctor of Computing, Lecturer, Department of Informatics, Tshwane University of Technology, Pretoria, South Africa. 51 International Journal of Science Annals, Vol. 7, No. 1, 2024 рrint ISSN: 2617-2682; online ISSN: 2707-3637; DOI:10.26697/ijsa Introduction In recent years, healthcare Small and Medium can contribute to SMEs’ dynamic capabilities Enterprises (SMEs) have become an essential (Engelmann, 2024; Khurana et al., 2022; Moyo & instrument for individuals in many countries across the Loock, 2021; Suhendi et al., 2020). According to recent globe (Fahmi et al., 2022; Raimo et al, 2023; Salisu et scholarly literature (Drydakis, 2022; Khurana et al., al., 2021). Additionally, healthcare sector SMEs 2022), DCs are substantial because they enable SMEs to improve the economy by providing services to patients, quickly detect market changes before their rivals do eradicating poverty, and generating new job (Warner & Wäger, 2019). Extant research found that in opportunities (Balta et al., 2021; Moretti et al., 2023). the SME sector, the development of DCs relies on Nonetheless, several scholars (Enesi & Ibrahim, 2021; sensing, seizing and reconfiguring (Khurana et al., 2022; Salisu et al., 2021) reported that the advent of COVID- Engelmann, 2024). From a business perspective, sensing 19 caused significant harm to various enterprises across focuses on discovering opportunities, seizing aims to the globe. In support of this viewpoint, empirical studies utilize the opportunities, and reconfiguring improve conducted globally reported that 60% of SMEs face the business models (Drydakis, 2022). With the help of challenge of liquidation and about 50% have stopped SaaS, healthcare sector SMEs can sense the opportunity operating because of the lockdown measures (Bularafa to collaborate with patients on the Internet (Suhendi et & Adamu, 2021; Trawnih et al., 2021). al., 2020; Spanò et al., 2023). Furthermore, SaaS can According to a plethora of research (Bularafa & Adamu, enable healthcare sector SMEs to seize the opportunity 2021; Khurana et al., 2022), while the COVID-19 of doing business on the Internet (Johnston et al., 2023). pandemic impacted various sectors, the healthcare Moreover, SaaS can help healthcare sector SMEs to SMEs have witnessed a severe impact due to their lack transform by reconfiguring their business models of technological resources. Consequently, healthcare (Engelmann, 2024; Majengo & Mbise, 2022). sector SMEs must use technology to enhance their In the epoch of the digital economy, web and Cloud- performance and survive in the face of exogenous based services may be tools to promote innovation and shocks (Preko & Boateng, 2020; Zimmermannova et al., enhance enterprises’ performance (Moyo & Loock, 2022). In recent years, enterprises’ use of Cloud services 2021; Suhendi et al., 2020). Empirical studies conducted and digital products (Pypenko, 2019) has become globally (Deloitte UK’s Centre for Health Solution, widespread (Aceto et al., 2020; Moyo & Loock, 2021; 2020; Nicolau et al., 2022; Raimo et al., 2023; Statista, Suhendi et al., 2020). The Internet enables healthcare 2023) affirm that the use of web and Cloud-based organisations to communicate with patients anytime and services (SaaS) can help healthcare organisations to anywhere (Deloitte UK’s Centre for Health Solution, improve the way in which they provide healthcare 2020; Raimo et al., 2023). One of those Cloud services services to patients (Balta et al., 2021; Moretti et al., is Software as a Service (SaaS) (Majengo & Mbise, 2023; Spanò et al., 2023). Yet, within South Africa, 2022; Mokwena & Hlebela, 2018; Moyo & Loock, there are limited studies on the use of SaaS to improve 2021). A plethora of scholarly literature elucidates that the DCs of healthcare SMEs. SaaS is viewed as a tool for facilitating communication The aim of the study. To develop the conceptual model mechanisms and drawing people together through for the use of SaaS to improve the DCs of healthcare sharing content (Alassafi, 2021; Loukis et al., 2019). SMEs. Extant research refers to SaaS as a Cloud service model The following study model was conceptualised from by that enables various sectors to rent information and triangulating the two theoretical models that were used communication technology (ICT) services from a Cloud as lenses for this study. The two theoretical models Service Provider (CSP) on the Internet (Khaki & Khan, underpinned by this study included Task-Technology 2023; Majengo & Mbise, 2022; Suhendi et al., 2020). Fit (TTF) and Fit Viability Model (FVM). The study Within the various sectors, SaaS has taken a substantial hypotheses (H1–H10) are shown in Figure 1. role in healthcare SMEs (Deloitte UK’s Centre for Health Solution, 2020; Moyo & Loock, 2021; Raimo et Materials and Methods al., 2023). Recent scholarly literature indicates that the To explain DCs and the use of SaaS by healthcare sector use of digital technologies (DTs) such as SaaS enables SMEs, positivism was identified as the most suitable the healthcare SMEs to improve healthcare services, paradigm for the study. A plethora of research (Creswell reduce costs, and have access to electronic health & Creswell, 2018; Hall et al., 2022; Hasan, 2016) records (Meri et al., 2019; Moretti et al., 2023; Moyo & pointed out that positivist studies are associated with Loock, 2021; Raimo et al., 2023; Suhendi et al., 2020). quantitative research approach that test hypotheses. The Additionally, several scholars (Moyo & Loock, 2021; present study utilized a survey questionnaire to collect Raimo et al., 2023) posit that DTs such as tele-health, data. The survey questionnaire used a five Likert scale electronic communications, web and Cloud-based method with anchors starting from 1 (strongly disagree) services, if implemented in a targeted manner, have the to 5 (strongly agree). Healthcare SMEs that had used potential to minimize health inequalities and improve SaaS form the population of this study. A survey people’s lives through a substantial change in the way in conducted by Small Enterprise Development Agency which healthcare services are provided to patients (Balta (SEDA, 2021) reported that the registered number of et al., 2021; Moretti et al., 2023; Spanò et al., 2023). SMEs in South Africa during the first quarter of 2021 Furthermore, other scholars posit that Cloud services was projected to be close to 786,027. 52 International Journal of Science Annals, Vol. 7, No. 1, 2024 рrint ISSN: 2617-2682; online ISSN: 2707-3637; DOI:10.26697/ijsa Figure 1 Conceptualized Study Model for the Use of SaaS to Improve the DCs of Healthcare SMEs Note. H1: Customer service influences the use of SaaS to improve the DCs of healthcare SMEs. H2: Sharing information influences the use of SaaS to improve the DCs of healthcare SMEs. H3: Internet access influences the use of SaaS to improve the DCs of healthcare SMEs. H4: Data security influences the use of SaaS to improve the DCs of healthcare SMEs. H5: Top management support influences the use of SaaS to improve the DCs of healthcare SMEs. H6: Finance influences the use of SaaS to improve the DCs of healthcare SMEs. H7: Competitive pressure influences the use of SaaS to improve the DCs of healthcare SMEs. H8: Infrastructure influences the use of SaaS to improve the DCs of healthcare SMEs. H9: Viability influences the use of SaaS to improve the DCs of healthcare SMEs. H10: Task-Technology Fit influences the use of SaaS to improve the DCs of healthcare SMEs. Scholarly work undertaken by Krejcie and Morgan meets a value of more than 0.7. As shown in Table 1, (1970) noted that a population that is between 75,000 Cronbach’s alpha meet the threshold requirements. and 1,000,000 is represented by a sample size of 384. As a result, the sample size of this present study was 384. Table 1 To evade non-respondent issues when collecting data. Reliability Result of the Data Collection Instrument The research team distributed 500 questionnaires to healthcare sector SMEs. A 60.0% response rate was attained from these questionnaires, with the participants answering 300 of the questionnaires. The collected data were analyzed using SPSS version 28. Reliability Analysis In this stage, a reliability test was conducted. Recent Healthcare SMEs in South Africa were the target scholarly works (Hair et al., 2019; Hall et al., 2022; respondents. The study envisioned to obtain data from Salah & Ayyash, 2023) point out that the principal five hundred (500) SMEs. Three hundred 300 responded reason for performing a reliability test is to examine the accordingly. level of consistency of the questionnaire. Additionally, Table 2 presents the demographical statistics of scholarly work by Hall et al. (2022) posit that the respondents. The demographic variables include gender, questionnaire is considered reliable if Cronbach’s alpha age (years), education and use of SaaS. 53 International Journal of Science Annals, Vol. 7, No. 1, 2024 рrint ISSN: 2617-2682; online ISSN: 2707-3637; DOI:10.26697/ijsa Table 2 Demographical Statistics of Respondents As shown in Table 2, 63.3% (187) of participants Measurement Model Analysis representing healthcare SMEs were males, whilst 37.7% Before assessing the structural model, measurement (113) were females. Furthermore, the findings in Table model analysis was conducted. A plethora of research 2 reveal that 74.0% (222) of participants were between (Khan et al., 2021; Kikawa et al., 2022; Maroufkhani et the ages of 20 to 30, 21.3% (64) were between 41 to 50 al., 2020; Steenkamp & Maydeu-Olivares, 2023; Yusoff and 4.7% (14) were above 50 years. et al., 2020) point out that measurement model analysis Regarding education, 56.7% (170) of participants had a is performed by using factor loadings (FL), composite B-tech, followed by 19.3% (58) who had a master's, reliability (CR), and average variance extracted (AVE). 15.3% (46) had a diploma, 6.7% (20) had a matric and As recommended by Hair et al. (2019) for the only 2.0% (6) had a PhD. measurement model test results to be acceptable, FL and Concerning the use of SaaS, 88.0% (264) of participants CR must meet a value of more than 0.7 and AVE a value revealed that they are using SaaS, whilst 12.0% (36) of more than 0.5. As displayed in Table 3, all the FL, alluded that they are not using SaaS. CR, and AVE values meet the threshold requirements. Table 3 Loadings Reliability and Validity Statistics Note. CUS – customer service; SHI – sharing information; IEA – internet access; DAS – data security; TMS – top management support; FIC – finance; CMP – competitive pressure; IFT – infrastructure; VAB – viability; TTF – task- technology fit. Assessment of Structural Model p<0.05), IEA (β=0.057, p<0.05), DAS (β=0.022, In this stage, structural equation modelling (SEM) was p<0.05), TMS (β=0.427, p<0.05), CMP (β=0.178, utilised. According to recent scholarly literature (Al- p<0.05), VAB (β=0.325, p<0.05) and TTF (β=0.032, Mamary, 2022; Kikawa et al., 2022; Steenkamp & p<0.05) have a positive effect on the use of SaaS. Whilst Maydeu-Olivares, 2023), SEM is used in research the hypotheses FIC (β=0.235, p>0.05) and IFT studies to test the hypotheses. (β=0.052, p>0.05) have a negative effect on the use of As displayed in Table 4, the SEM results show that the SaaS. hypotheses CUS (β=0.125, p<0.05), SHI (β=0.132, 54 International Journal of Science Annals, Vol. 7, No. 1, 2024 рrint ISSN: 2617-2682; online ISSN: 2707-3637; DOI:10.26697/ijsa Table 4 Hypotheses Testing Note. *p<0.05; **p<0.01; CUS – customer service; SHI – sharing information; IEA – internet access; DAS – data security; TMS – top management support; FIC – finance; CMP – competitive pressure; IFT – infrastructure; VAB – viability; TTF – task-technology fit. As displayed in Table 4 and Figure 2, eight hypotheses two hypotheses (H6 and H8) were not supported (H1, H2, H3, H4, H5, H7, H9, and H10) were supported because they have a p-value of greater than >0.05. because they have a p-value of less than <0.05, while Figure 2 A Model for the Use of SaaS to Improve the Dynamic Capabilities of South African Healthcare sector SMEs Results and Discussion Task Characteristics The model (Figure 2) shows the factors that are The study results in Table 4 show that CUS significant to the use of SaaS to improve the dynamic (p=0.022<0.05) has a positive effect on the use of SaaS capabilities (DCs) of South African healthcare SMEs. to improve the DCs of healthcare sector SMEs. 55 International Journal of Science Annals, Vol. 7, No. 1, 2024 рrint ISSN: 2617-2682; online ISSN: 2707-3637; DOI:10.26697/ijsa Therefore, H1 is supported. This outcome is in line with Task-Technology Fit Raimo et al. (2023) who found that web and Cloud- The positive effect of TTF (p=0.000<0.05) on the use of services helped healthcare organisations in Italy to SaaS is also confirmed. Therefore, H10 is supported. improve customer service. In addition, the present study This outcome in line with Wang et al. (2019) who found proved that SHI (p=0.000<0.05) has positive effect on the that TTF play a substantial role in the use of Big Data use of SaaS. Therefore, H2 is supported. In support of Analytics (BDA) mobile cloud healthcare system. this outcome, a plethora of research (Mokwena & Hlebela, 2018; Moyo & Loock, 2021; Raimo et al., 2023) Conclusions point out that SaaS can help healthcare sector SMEs to In this paper, the conceptual model is proposed to share information with their patients. identify and explain the factors influencing the use of Technology Characteristics Software as a Service (SaaS) to improve the dynamic As displayed in Table 4, IEA (p=0.014<0.05) has a capabilities (DCs) of healthcare SMEs. This model is positive effect on the use of SaaS. Therefore, H3 is based on Task-Technology Fit (TTF) and Fit Viability supported. Recent scholarly works (Johnston et al., 2023; Model (FVM) and some external constructs Khaki & Khan, 2023; Raimo et al., 2023) have shown (organisational characteristics and environment that having access to the internet can help organisations, characteristics). The study results show that customer particularly healthcare sector SMEs to improve the DCs service (CSE), sharing information (SHI), internet access (Hercheui & Ranjith, 2020; Pietronudo et al., 2022; (IEA), data security (DAS), top management support Suhendi et al., 2020; Weaven et al., 2021). Similarly, the (TMS), competitive pressure (CMP), viability (VAB) positive effect of DAS (p=0.003<0.05) on the use of SaaS and task-technology fit (TTF) play a positive role on the is confirmed. Therefore, H4 is supported. This outcome use of SaaS to improve the DCs of healthcare SMEs. is supported by Ganiga et al. (2018) and Mubarakali et al. However, the present study also found that finance (FIC) (2020) who pointed out that Cloud services can help and infrastructure (IFT) play a negative role on the use of healthcare organisations to manage and protect the data SaaS to improve the DCs of healthcare SMEs. This paper of patients. concludes that SaaS is key to improving DCs of Organisational Characteristics healthcare sector SMEs. As displayed in Table 4, TMS (p=0.000<0.05) has a positive effect on the use of SaaS. Therefore, H5 is Acknowledgments supported. This outcome is consistent with Nassoura The authors would like to express their gratitude to all (2020) who found that top management support (TMS) participating healthcare SMEs. Their participation helped play a substantial role on the adoption of Cloud provide further insights to Software as a Service and Computing in Jordanian healthcare organisations. dynamic capabilities, notably in the context of South However, the present study found that FIC African SMEs. (p=0.732>0.05) has a negative influence on the use of SaaS. Therefore, H6 is not supported. This outcome is Ethical Approval consistent with Khurana et al. (2022) who argued that The study obtained ethical clearance from the digital technologies (DTs) are not easy to adopt, because institution’s Ethics Committee (Ref NO. the majority of SMEs lack funding. FCRE/ICT/2022/03/001 (1). Environmental Characteristics On the other hand, the present study found that CMP Funding Source (p=0.000<0.05) has a positive effect on the use of SaaS. The present study received no specific funding from any Therefore, H7 is supported. This outcome is in line with public, private, or non-profit organisation. Raimo et al. (2023) who found that healthcare organisations use Cloud-services in reaction to the References increase in competitive pressure (CMP) which is fueled Aceto, G., Persico, V., & Pescapé, A. (2020). Industry by the danger of losing customers. 4.0 and health: Internet of things, big data, and However, the study found that IFT (p=0.853>0.05) has a cloud computing for healthcare 4.0. Journal of negative effect on the use of SaaS. 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Building dynamic Digitalisation in hospitals in COVID-19 times – A capabilities for digital transformation: An case study of the Czech Republic. Economies, ongoing process of strategic renewal. Long Range 10(3), Article 68. https://doi.org/10.3390/economies10030068 Cite this article as: Makelana, P., Kekwaletswe, R., & Segooa, M. A. (2024). Conceptualizing a model for the use of software as a service to improve the dynamic capabilities of small and medium enterprises in healthcare sector. International Journal of Science Annals, 7(1), 51–59. https://doi.org/10.26697/ijsa.2024.1.5 The electronic version of this article is complete. It can be found online in the IJSA Archive https://ijsa.culturehealth.org/en/arhiv This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (http://creativecommons.org/licenses/by/4.0/deed.en). 59