PurposeThis study intends to reveal how to manage the dynamic process of information technology business (IT-business) strategic alignment; managing this alignment is an unknown yet critical issue that must be addressed by any firm trying to unleash the business value of their IT investments.Design/methodology/approachThis study presents our case study of a healthcare organization after healthcare information systems (HIS) implementation and investigates the strategic alignment between the implemented HIS and the organizational strategy from a dynamic perspective.FindingsTwo different patterns of alignment (i.e. an IT-strategy–driven pattern and a business-strategy–driven pattern) are identified, and a process model of the IT-business strategic alignment is developed. Moreover, this study focuses on the social dimension of strategic alignment and examines the role of this dimension, which is critical and fundamental with respect to other dimensions, in achieving strategic alignment.Research limitations/implicationsThis paper makes important theoretical contributions to the understanding of strategic alignment by taking a dynamic view of alignment, identifying different patterns of alignment, emphasizing the role of social alignment and developing a comprehensive process model.Practical implicationsFrom a managerial perspective, managers should periodically scrutinize the IT-business alignment patterns of their organizations and develop dynamic capabilities for strategic alignment.Originality/valueWhile most of the literature on the dynamics of strategic alignment have focused on confirming the dynamics of strategic alignment and identifying the factors that create dynamics in alignment, this study examines IT-business alignment as a continuous process over time, thus providing a novel perspective. Moreover, while the role of social alignment and its impact on downstream performance remain unclear in the current literature, this study incorporates the social dimension of alignment to investigate the role of this dimension in achieving IT-business strategic alignment.
Although credit card overspending behavior has become a critical societal concern with severe negative impacts on consumer welfare and economic stability, research on credit card overspending behavior remains fragmented and understudied. This study investigates new types of antecedents of credit card overspending behavior that are overlooked in the prior literature—the acquisition mode of credit card companies. Based on data set from a large commercial bank in China, this study measures credit card overspending behavior using consumption amount, cash withdrawal amount and overdueness, and suggests that gift acquisition has a positive effect on cash withdrawal amount and overdue probability as well as a negative effect on consumption amount. Furthermore, we find that this relationship could be weakened for female customers and for customers with higher education levels. This study provides theoretical implications for both the credit card overspending literature and customer acquisition literature. It also has important implications for consumer welfare and public policymaking.
AI-enabled blockchain refers to the use of AI to enable the analysis and decision-making processes based on data collected, shared, and stored by blockchain. This helps overcome some of the existing challenges in blockchain applications. Despite the growing number of review papers on blockchain and AI, there is a dearth of literature on AI-enabled blockchain in business scenarios. This study uses bibliometric-content analysis to (1) identify three stages of development of AI-enabled blockchain literature and point out the increasing diversity of technological applications; (2) identify the strongest foci of extant literature; (3) unveil the roles of AI-enabled blockchain in 10 application sectors, and identify the key roles of AI in enabling blockchain applications; (4) conclude the referred ethical issues from three levels and make further discussion. The findings present the trends of AI-enabled blockchain and could help developers and service providers better manage the use and ethical issues of AI in blockchain applications.
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