The Effect of Artificial Intelligence on Organisational Creativity and Performance Within Electronic Commerce Businesses

1. INTRODUCTION

Strategic deployment of emerging technologies can be considered as a major advantage for businesses that seek to outperform competitors. For example, artificial intelligence (AI) is shifting the business landscape, economic systems, and social structures by redefining interactions and engagements between stakeholders and consumers (Loureiro et al., 2021).¹ According to Luo (2023),² businesses should increase their use of AI technologies to improve their operational productivity as well as their ability to generate higher value for consumers. However, the use of AI and other emerging technologies requires substantial financial resources and the hiring of sophisticated workforce that has advanced technical competencies. According to Prasetyanto et al. (2024),³ effective implementations of AI to support creative performance necessitate substantial organisational realignment and substantial resources for improving the skills of the workforce and the organisational technological infrastructure. One study reveals that AI can fundamentally reshape economic systems, with forecasts indicating potential contributions of $15.7 trillion to the world economy by 2030 (PwC, 2020).⁴ AI-driven transformation may reform industry landscapes, with significant implications for many sectors, including manufacturing, logistics, finance, retail, healthcare, utilities, and supply chain management (Dwivedi et al., 2021).⁵ The AI sector achieved a record in investment levels of $252.3 billion USD in 2024, with 26 percent overall growth driven by a 44.5 percent increase in private investment and a 12.1 percent increase in in mergers and acquisitions (Maslej et al., 2025).⁶

AI can be implemented in any business, including in electronic commerce (e-commerce) businesses, to enhance productivity and boost performance. Implementing AI technologies in e-commerce ecosystems may lead to substantial innovation in areas like customer experience, customised interactions, logistical operations, marketing practices, and service delivery, which could reshape consumer engagement in digital retail environments. This research focuses on businesses that sell products or services online through e-commerce, which is forecast to generate more than $4.3 trillion USD in sales by the end of 2025 and to continue growing rapidly (Gelder, 2025).⁷ The use of AI technologies in the e-commerce field supports firms’ ability to conduct in-depth analyses of consumers’ behaviour, including their shopping habits, interests, and preferences, all of which help e-commerce businesses to deliver personalised customer experiences (Chaudhari & Hajare, 2024).⁸ E-commerce businesses can also implement AI technologies to support other business functions and increase organisational creativity and performance.

The use of AI to develop and maintain competitive advantage has emerged as a research priority for both academic researchers and business practitioners (Borges et al., 2021).⁹ However, few studies examine the impact of AI adoption on business performance measures empirically (Mikalef & Gupta, 2021).¹⁰ Cheng et al. (2023)¹¹ suggest that, with the global shift to AI, future studies should explore the value and potential use of AI in the context of e-commerce. The current research looks at the AI capability effects on the organisational creativity and performance of e-commerce businesses. In doing so, this research contributes to the literature by validating and extending an existing research model that examines the effects of AI capability and organisational creativity on organisational performance. The next section provides a literature review and defines important concepts, after which the research model as well as hypotheses are presented. The research method section follows in section 4. After that, the research results are presented in the next section. Then, section 6 discusses the research results, followed by section 7, which includes the limitations of the current research and presents some directions for future research.

2. LITERATURE REVIEW

Organisations that seek to advance their technological infrastructure to compete and stay in business use emerging technologies like AI to empower employees and achieve their goals. For example, Maslej et al. (2024)¹² show that AI enables employees to accomplish their work more efficiently with better quality and helps to level the differences in employees’ skills. Another example of AI applications in e-commerce businesses is AI-driven chatbots, which enhance the quality of human interactions and help to ensure continuous customer engagement (Lee & Park, 2022).¹³ Through the employment of AI-powered analytical insights, e-commerce businesses can interpret market trends and consumer behaviour in real time, thus promoting a responsive innovation ecosystem for sustainable business development (Oyekunle & Boohene, 2024).¹⁴ Moreover, AI implementation can improve decision-making processes, encourage innovation, increase productivity, and optimise operations, which may lead to overall improvement in managing businesses (Rane et al., 2024).¹⁵

Lahoti (2023)¹⁶ reveals that businesses that adopt AI-driven strategic initiatives lead to statistically significant improvements in operational efficiency and performance outcomes. However, Maslej et al. (2025)⁶ revealed that businesses that report AI’s functional applications, which have financial effects, see few benefits of such implementations, and the fact that AI applications also face challenges that include risks related to privacy and data governance.

There are four types of AI, which are assisted intelligence, augmented intelligence, automated intelligence, and autonomous intelligence (PwC, 2020).⁴ On the other hand, Russell and Norvig (2016)¹⁷ categorise four types of AI systems along the two key dimensions of human performance–rationality and reasoning–behaviour: systems that are designed to think like humans, systems that replicate human actions, systems that are designed to think rationally, and systems that are designed to act rationally. To define what AI means, this study adopts Mikalef and Gupta (2021)¹⁰ definition of AI as “a system [that can] identify, interpret, make inferences, and learn from data to achieve predetermined organisational and societal goals”. In addition, another important definition that is needed for this research is e-commerce. DeLone and McLean (2004)¹⁸ define e-commerce as “the use of the Internet to facilitate, execute, and process business transactions”.

There are a number of studies aiming to conduct a literature review on the application of AI in the e-commerce context (Bawack et al., 2022;¹⁹ Boukrouh & Azmani, 2024²⁰; Chugh & Jain, 2024²¹; Fedorko et al., 2022²²; Richard et al., 2025²³; Saleem & Naseem, 2023).²⁴ Moreover, other studies also address the deployment of AI in e-commerce, with an emphasis on AI’s practical applications, role, usage trends, and impact (Cheng et al., 2023;¹¹ Gupta et al., 2024;²⁵ Haidar, 2024;²⁶ Harshitha et al., 2024;²⁷ He et al., 2024;²⁸ Kashyap et al., 2022;²⁹ Lari et al., 2022;³⁰ Rashidin et al., 2021).³¹ However, the literature lacks theoretical frameworks for building organisational AI capability (Mikalef & Gupta, 2021),¹⁰ and studies on AI-driven technology innovation in e-commerce and digital economic systems remain preliminary (Cheng et al., 2023).¹¹ Moreover, Kashyap et al. (2022)²⁹ reveal a research gap regarding the deployment of AI technologies in e-commerce contexts.

Mikalef and Gupta (2021)¹⁰ propose a theoretical framework, which is based on the resource-based theory (RBT), and develop an instrument for evaluating AI in organisations, with the objective of examining the effects of AI capability on organisational creativity and performance. They define AI capability (AIC) as “the ability of a firm to select, orchestrate, and leverage its AI-specific resources” (Mikalef & Gupta, 2021).¹⁰ In addition, they propose that AIC resources can be categorised into three main types of resources: firstly, tangible resources, including basic resources, technology, and data; secondly, human resources, which consist of technical skills and business skills; and finally, intangible resources, which cover risk proclivity, organisational capacity for change, and inter-departmental coordination. Table 1 provides further descriptions of these AIC resources. Mikalef and Gupta (2021)¹⁰ also emphasise that each of these resources should be owned by the company or at least acquired through another party. AIC extends the traditional view of AI as it includes all the needed resources that are substantial for the successful implementation of AI (Enholm et al., 2022).³²

Mikalef and Gupta (2021)¹⁰ defined organisational creativity as “the degree to which an organisation is able to generate new and constructive ideas (or products) in the complex organisational setting”. Researchers across multiple industries confirm that developing AIC can serve as a driver for enhanced creativity within organisations (Amabile, 2020).³³ Moreover, according to Raisch and Krakowski (2021),³⁴ the strategic implementation of AI technologies enables managerial insight by analysing complex datasets to reveal previously inaccessible patterns and correlations. Using such technologies in the right way may result in improving organisational creativity. AI-derived insights can directly yield creative outcomes at the organisational level (Paschen et al., 2020).³⁵ Furthermore, Mikalef and Gupta (2021)¹⁰ revealed that AIC has a significant influence on organisational creativity.

Having the right AIC will not only improve organisational creativity, but it might also positively affect organisational performance. Mikalef and Gupta (2021)¹⁰ defined organisational performance as “the degree to which organisations achieve their business objectives”. Chen et al. (2022)³⁶ apply the resource-based view to explore the relationship between AIC and company performance in the e-commerce context, and they revealed that AIC affects these companies’ performance, mediated by AI-enabled decision-making, organisational creativity, and AI management. In addition, Fosso Wamba et al. (2024)³⁷ also apply the resource-based view to reveal that AIC directly influences firm performance and indirectly affects firm performance, mediated by data-driven culture. Furthermore, Okonji et al. (2023)³⁸ examine the role of organisational creativity in the relationship between AIC and organisational performance and show a significant positive association between AIC and organisational performance. Moreover, Mikalef and Gupta (2021)¹⁰ revealed that AIC has a significant influence on organisational performance.

Rumanti et al. (2023)³⁹ empirically confirm the significant positive effect of both organisational creativity and open innovation on small and medium-sized enterprises’ performance. The authors expand the organisational creativity construct by suggesting that it consists of four factors: internal organisational environment, individual creativity, knowledge creation, and group creativity (see Table 2 for more details). This expanded view of the organisational creativity construct will be adopted in this study to extend the work of (Mikalef & Gupta, 2021).¹⁰

Previous studies consistently highlight creativity as a vital contributor to enhanced organisational performance and long-term success (Boso et al., 2017).⁴⁰ Moreover, Ferreira et al. (2020)⁴¹ argued that the positive effect of creativity on performance is substantial but operates through indirect mechanisms, while Weinzimmer et al. (2011)⁴² proposed that the relationship is direct. In addition, Riaz and Hassan (2019)⁴³ propose a direct, positive association between an organisation’s creative capacity and its overall performance. Moreover, Mikalef and Gupta (2021)¹⁰ reported that organisational creativity has a significantly positive influence on organisational performance. Based on the previous discussion, the following hypotheses were developed:

• H1: Artificial intelligence capability has a significantly positive influence on organisational creativity within e-commerce businesses.

• H2: Artificial intelligence capability has a significantly positive influence on organisational performance within e-commerce businesses.

• H3: Organisational creativity has a significantly positive influence on organisational performance within e-commerce businesses.

3. RESEARCH FRAMEWORK AND SURVEY INSTRUMENT

Mikalef and Gupta (2021)¹⁰ develop a theoretical framework and an instrument that can be used to measure an organisation’s AIC to examine AIC’s influence on organisational creativity and organisational performance. In addition, Rumanti et al. (2023)³⁹ expanded the organisational creativity construct to include sub-variables as mentioned in the previous section. Using data from e-commerce businesses, the present research validates the theoretical framework suggested by (Mikalef & Gupta, 2021)¹⁰ and extends it based on Rumanti et al. (2023)³⁹ work. Figure 1 presents the proposed theoretical model for this research, and it includes the proposed research hypotheses.

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Figure 1:

The proposed research model by Mikalef & Gupta, 2021; Rumanti et al., 2023.

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To validate the proposed research model and examine the proposed research hypotheses, a survey questionnaire was designed as presented in Appendix 1. The survey questionnaire was then used to measure the research constructs presented in Figure 1. The next section of this paper presents the research methodology that was applied.

4. RESEARCH METHODOLOGY

As Field (2013)⁴⁴ and Hair et al. (2010)⁴⁵ suggest, quantitative research methods—mainly structural equation modelling (SEM) were used to validate the proposed research model and examine the three research hypotheses. The survey questionnaire presented in Appendix 1 was used to collect the primary research data. The survey questionnaire is divided into four main sections. The first section contains demographic questions. The other three sections contain questions about participants’ level of agreement, by applying a 5-point Likert scale where “1 = Strongly Disagree and 5 = Strongly Agree”, with the items which were designed to measure the research constructs, which are presented in the research model presented in Figure 1 (See Appendix 1 for more details).

The distribution of the survey questionnaire was anonymous, and it does not collect any personally identifiable or sensitive information, nor does it involve minimal risk to participants. Before participating in the survey, participants were provided with a participant information sheet that defined the study purpose, data handling procedures, and their rights, including voluntary participation and the ability to withdraw from participating in the survey. Additionally, proper consent was obtained explicitly from all participants before proceeding with the survey, as well as having the option to withdraw from participating in the survey.

The survey was distributed via the Prolific platform to participants who are currently working, hold current or have held previous managerial positions, have experience applying technology and using AI systems or software in their work, and are currently working in companies that provide services or sell products online. Prolific also assists in the screening process to select appropriate participants. In addition, some screening questions were added to the questionnaire to verify that participants met the screening criteria. After the collected data were evaluated, 355 responses were considered valid and analysed using statistical package for the social sciences (SPSS) and analysis of moment structures (AMOS) statistical software packages. Table 3 presents the demographic profile of the participants in this study. The next section highlights the research results of the analysis.

To ensure that the survey questionnaire is a reliable measure of the constructs, Cronbach’s alpha test was applied. The result was a Cronbach’s alpha of 0.977 for the whole questionnaire, which is greater than 0.7 and considered acceptable (Field, 2013).⁴⁴ In addition, as presented in Table 4, Cronbach’s alpha for each construct was greater than 0.7 and considered acceptable (Field, 2013).⁴⁴ Thus, the survey questionnaire is considered a reliable measure for all the constructs (See Table 4 for more details).

5. RESULTS

Confirmatory factor analysis (CFA) using AMOS was then applied to assess the validity of the proposed research model presented in Figure 1 as well as “testing how well a prespecified measurement theory composed of measured variables and factors fits reality as captured by data” (Hair et al., 2019, p. 660).⁴⁶ To apply the CFA, first, the model was created, and the collected data was loaded onto the model. Then the CFA was conducted, the results of which are presented in Table 5.

As shown in Table 5, the result of CFA shows the model fit as indicated by CFI (0.921), IFI (0.922), TLI (0.917), and RMSEA (0.042), which appears as acceptable based on (Dion, 2008;⁴⁷ Hu & Bentler, 1999).⁴⁸ Also, the CMIN/DF (1.636), which is also acceptable as it is below 3 (Dion, 2008;⁴⁷ Hu & Bentler, 1999).⁴⁸

To determine the validity of the CFA analysis, convergent and discriminant validity tests were also applied. These tests include assessments of average variance extracted (AVE), average shared variance (ASV), composite reliability (CR), and maximum shared variance (MSV). Table 6 presents the results of these tests, which show that the research model does not have convergent or discriminant validity concerns. Moreover, a multicollinearity test—a variance inflation factor (VIF) test—was also conducted. The results are acceptable, as the VIFs were below 5 for all three constructs (Hair et al., 2010).⁴⁵

Path analysis using AMOS was then conducted to validate the research hypotheses. As Table 7 shows, all three hypotheses (H1, H2, and H3) are supported as p-value for all three hypotheses were significant. Therefore, we conclude that AIC has a positive and significant influence on organisational creativity within e-commerce businesses. Moreover, the results confirmed that AIC has a significant positive influence on organisational performance within e-commerce businesses. In addition, we can confirm that organisational creativity has a significant and positive influence on organisational performance within e-commerce businesses.

A test for interpretational confounding was also performed as suggested by Kim et al. (2010)⁴⁹ by creating two models in order to test the two paths AIC to OC and AIC to OP presented in Figure 1, which shows a multiple indicators multiple causes model. This test was conducted to make sure interpretational confounding does not exist. As illustrated in Figure 2, the weights of the three formative measures that encompass the AIC construct are consistent and statistically significant across the two models, which is acceptable according to Hair et al. (2019).⁴⁶

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Figure 2:

Test for interpretational confounding. *** Signifies p ≤ 0.001

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6. DISCUSSION

As many businesses implement systems that are powered by AI technologies, the current research investigates the influence of AIC on organisational creativity as well as the influence of AIC and organisational creativity on organisational performance in e-commerce businesses. This paper contributes to the literature by validating a research model developed by Mikalef and Gupta (2021)¹⁰ and extending it by expanding the measures of the organisational creativity construct to include the internal organisational environment, individual creativity, group creativity, and knowledge creation, as Rumanti et al. (2023)³⁹ suggested.

As shown in the results of the analysis, the proposed model and the survey instrument can be considered as valid and reliable measures. Based on the results of the analysis, the three proposed research hypotheses were accepted. The results revealed that AIC has a positive and significant influence on organisational creativity within e-commerce businesses, which is aligned with the results of (Chen et al., 2022;³⁶ Mikalef & Gupta, 2021;¹⁰ Okonji et al., 2023).³⁸ As discussed, AIC requires several types of resources, including data, basic resources, technology, business skills, technical skills, inter-departmental coordination, organisational capacity for change, and a reasonable level of risk proclivity, so developing AIC can be a big and costly task that needs time. However, once organisations obtain AIC and its related resources are ready, AIC can have a positive influence on organisational creativity, which in turn can be useful in developing new products and services or advancing existing ones. Boosting organisational creativity, through obtaining the right AIC, can be a forerunner to organisational innovation (Anderson et al., 2014;⁵⁰ Sarooghi et al., 2015).⁵¹ Clearly, e-commerce businesses, as well as others, should invest in the resources they need to develop AIC, which in turn will impact organisational creativity.

AIC can also support the development of AI technologies as it has many applications within e-commerce businesses, including enquiry resolution, recommendation systems, chatbots, marketing automation, predictive analytics, personalisation of products and services, customer review management, virtual assistants, and other kinds of automation (Gupta et al., 2024; Kashyap et al., 2022). Developing the right AI technologies can also have many implications on management as it will boost efficiency, as well as it will improve data analysis techniques to get better insights. It is recommended that e-commerce businesses plan for and implement AI to advance the value of their services and obtain sustainable competitive advantages.

The results of the analysis also revealed that AIC has a significantly positive influence on organisational performance within e-commerce businesses. This result is aligned with those of (Fosso Wamba et al., 2024; Mikalef & Gupta, 2021; Okonji et al., 2023). Having the right AIC can help e-commerce businesses increase their market share, growth rates, and profitability, and boost innovation to gain a competitive advantage. Therefore, we conclude that e-commerce businesses that seek to outperform their competitors should acquire the right resources that they need to develop their AIC and implement AI technologies to achieve their objectives. Indeed, managers seeking to achieve higher performance should pay attention to developing the organisational AIC, which in turn will positively impact organisational performance.

Finally, the results of the analysis revealed that organisational creativity has a significantly positive influence on organisational performance within e-commerce businesses, a result that is aligned with those of (Mikalef & Gupta, 2021; Rumanti et al., 2023). As discussed, several factors—the internal organisational environment, individual creativity, knowledge creation, and group creativity—can contribute to achieving organisational creativity, which then influences organisational performance. E-commerce businesses should enhance their organisational performance through AIC and organisational creativity if they wish to compete and become more profitable and innovative. Thus, leadership within e-commerce businesses and other businesses should promote creativity to be an essential strategic priority through the inclusion of creative capacity within the organisation’s mission, vision, and strategy.

7. CONCLUSION

The use of emerging technologies like AI can help businesses to become more competitive. AI can be applied in such a way as to be aligned with strategic business goals. The successful application of AI technologies in e-commerce businesses can help them improve their customers’ experience, facilitate personalisation of products and services, optimise operations, provide creative marketing practices, and optimise the delivery of products and services.

This research contributes to the literature by proposing an enhanced research model that extends an existing model to test AIC’s influences on organisational creativity and performance. An analysis shows that AIC has a positive and significant influence on both organisational creativity and organisational performance within e-commerce businesses, as well as that organisational creativity has a positive and significant influence on these businesses’ organisational performance. These results suggest that e-commerce businesses can increase their organisational creativity and performance by enhancing their AIC and using the results of this research to make informed decisions regarding the type of resources they can obtain to enhance their AIC and improve their organisational creativity and performance.

One of this paper’s limitations is that the research focuses only on e-commerce businesses. Future research can apply and test the proposed research model in other settings or on other types of businesses or propose new constructs or variables that may affect organisational creativity and performance, thus improving the proposed research model.