Issue #2 (Volume 17 2026)

Type of the article: Research Article

Abstract
The study aims to assess the effect of digital maturity, digital marketing, customer engagement, and brand trust on corporate reputation in Jordan’s insurance industry. A structured questionnaire was used to collect the data from 423 people selected from executive management, information technology, marketing, customer service, and digital transformation departments in insurance companies in Jordan. A quantitative research design was employed to cater to the requirement of analysis, and a total of 401 valid responses were gathered and analyzed using structural equation modeling (SEM) by employing the AMOS version 24. The results showed that digital maturity and digital marketing had a significant impact on corporate reputation, and customer engagement turned out to be the most important one. Brand trust also has a positive and significant effect on the development of reputation. Confirmatory factor analysis (CFA) was used to confirm construct reliability and validity findings based on the results of all Cronbach’s alpha values being greater than 0.80, as well as composite reliability and average variance extracted values meeting acceptable thresholds. The results showed an acceptable fit for the structural model in terms of RMSEA (0.047), CFI (0.944), TLI (0.932), and chi-squared values (2.21). The results indicate that reputation building in the insurance business requires coordinated digital solutions that enhance engagement, trust, and technological maturity.

Type of the article: Research Article

Abstract
The role of trust in social media platforms has gained increasing importance in the Iraqi insurance sector, as digital transformation is still in its early stages and customers are striving to build trust in digital platforms. This study aims to investigate the impact of customer trust in social media on perceived value and whether customer engagement mediates between the impact of customer trust in social media and perceived value in the context of an Iraqi insurance company. The study employed a quantitative cross-sectional design, and data were collected from 420 customers of Iraqi insurance companies who had previously used social media platforms. A self-administered online questionnaire was designed and distributed to residents in various Iraqi governorates using purposive sampling between August and November 2025. Partial least squares structural equation modeling (PLS-SEM) was used to test the proposed relationship. The results show that customer engagement (β = 0.503, p < 0.001) and perceived value (β = 0.450, p < 0.001) are positively and statistically significantly influenced by customer trust in social media platforms. Customer engagement (β = 0.244, p < 0.001) also positively influences their perceived value. Furthermore, customer engagement fully mediates the relationship between customer trust in social media platforms and perceived value (β = 0.120, p < 0.001). These findings offer an important lesson for insurance companies in Iraq seeking to better engage customers through their digital channels.

Type of the article: Research Article

Abstract
Cash flow volatility is an important source of financial uncertainty because unstable operating cash flows may weaken firms’ ability to meet obligations, sustain investment, and preserve financial flexibility. This issue is particularly relevant in emerging markets, where firms often face financing constraints and sectoral structure may shape financial stability differently. This study examines the relationship between cash flow volatility and financial stability in Jordanian listed firms and investigates whether the insurance sector responds differently to operating cash flow uncertainty compared with other non-financial firms. Financial stability is measured using the Z-score, while cash flow volatility is calculated as the rolling standard deviation of operating cash flow scaled by average total assets. The analysis uses panel data for Jordanian listed firms over 2014–2024. A three-year rolling window is applied in the baseline model, while a five-year rolling window is used as a robustness check. The regression model includes an interaction term between cash flow volatility and an insurance-sector dummy, along with firm size, leverage, firm age, and sales growth as control variables. The results indicate statistically weak evidence that the Z-score is negatively associated with cash flow volatility, albeit in a directionally weak one. But this is not statistically significant in the baseline fixed-effects model. Furthermore, the interaction between cash flow volatility and the insurance sector dummy is not statistically significant and has a different sign in one robustness specification. The study therefore does not confirm that insurance firms are structurally less sensitive to cash flow volatility. Leverage remains the most robust determinant of lower financial stability.

Acknowledgment
This research was funded through the annual funding track by the Deanship of Scientific Research, from the vice presidency for graduate studies and scientific research, King Faisal University, Saudi Arabia [Grant No. KFU263523].

Type of the article: Research Article

Abstract
Artificial intelligence is diffusing across Gulf Cooperation Council insurance markets, yet disclosure-based evidence remains fragmented on whether adoption is associated with organizational change or localized automation. This study examines a purposive disclosure-based sample of 120 insurers from Saudi Arabia, the United Arab Emirates, Qatar, Kuwait, Oman, and Bahrain. Because inclusion required sufficient disclosure of artificial intelligence practices, the sample is not intended to represent the insurance market. The study examines whether disclosed artificial intelligence adoption is associated with organizational change through financial transparency and operational efficiency. The dataset is constructed from annual reports, audited financial statements, governance reports, environmental, social, and governance reports, investor materials, and regulatory documents. Documents from 2017 to 2023 are treated as an observation window, coded at the item level, and aggregated into one firm-level score per insurer for cross-sectional structural equation modeling. Results indicate positive associations from artificial intelligence adoption to financial transparency (β = 0.52, p < 0.001) and operational efficiency (β = 0.49, p < 0.001). Financial transparency (β = 0.41, p = 0.003) and operational efficiency (β = 0.38, p = 0.012) are associated with organizational change. The indirect paths through transparency and efficiency are statistically distinguishable from zero within the model. Because all variables are derived from similar disclosure evidence, the pattern is interpreted as disclosure co-patterning rather than proof of a mechanism. The findings are associational, not causal, representative, or longitudinal.