THE INTEGRATION OF TECHNOLOGY IN BUSINESS PARTNERSHIPS: A NEW ERA OF STRATEGIC COLLABORATION
DOI:
https://doi.org/10.1234/aira.v2i1.42Keywords:
Chatbot partnerships, Human-technology integration, Artificial intelligence, Business effectiveness, Technological functionality, Strategic compatibility, Organizational culture, Sociotechnical systemsAbstract
This study investigates the impact of multiple determinant factors on the effectiveness of chatbots as business partners, focusing on organizational implementation contexts across diverse industries. As chatbot technologies evolve from basic customer service tools to sophisticated business partners capable of augmenting organizational capabilities, understanding the multifaceted determinants of their effectiveness becomes increasingly critical for successful implementation. The research addresses a significant gap in the literature by simultaneously examining technological, organizational, human-centered, strategic, and ethical dimensions of chatbot partnerships. Using a quantitative correlational approach, data were collected from 100 business professionals in managerial positions with direct involvement in chatbot implementation decisions across various industry sectors. A structured questionnaire with 5-point Likert scales measured the five independent variables and business partnership effectiveness, with analysis performed using IBM SPSS Statistics version 26. Comprehensive validity testing (r > 0.195), reliability testing (Cronbach's Alpha > 0.70), and classical assumption tests confirmed the appropriateness of the measurement instrument. Multiple regression analysis revealed that Human-Technology Integration (t = 5.013, p < 0.001), Technological Functionality (t = 4.333, p < 0.001), Strategic Compatibility (t = 4.176, p < 0.001), and Organizational Culture (t = 1.827, p = 0.071) positively influenced Business Partnership Effectiveness, while Ethical Transparency (t = 1.565, p = 0.121) did not demonstrate statistical significance. The overall model was highly significant (F = 28.679 > F-table 2.31, p < 0.001) with substantial explanatory power (R² = 0.603). This research contributes to socio-technical systems theory by establishing a hierarchical framework of chatbot partnership determinants, provides organizational leaders with evidence-based implementation priorities emphasizing humantechnology collaborative dynamics, and establishes a foundation for future research on AI-human partnerships across various business contexts.
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