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Software process tailoring (SPT) plays a critical role in contemporary software development. Because SPT determines how a software project proceeds, its effectiveness should be investigated. Specifically, SPT is a collaborative yet highly conflictual process, and the existing literature has paid little or no attention to how team members coordinate and to how power distance (PD) influences coordination under this conflictual situation for the purpose of fostering SPT effectiveness.

A propositional research method is utilized by reviewing the extant literature regarding SPT, team coordination and PD. Accordingly, several propositions are developed to theorize the contributive and moderating effects of team coordinative capabilities and PD on SPT effectiveness.

This study advances the understanding of the underlying mechanisms of the four distinct coordination capabilities in performing SPT, which will help software firms comprehend the moderating effects of PD on the relationships among coordinative capabilities and SPT effectiveness.

This study extends coordination theory and reveals four coordination capabilities that nurture SPT effectiveness. Moreover, this study demonstrates how power plays a role in the coordination of a team through the collaborative yet divergent SPT decision process to yield an integrative tailoring solution. In particular, we take a fresh viewpoint of PD considering the member-member relationship in exploring its moderating effects in the SPT context.

Due to the popularity of mobile devices and the development of artificial intelligence (AI), AI-powered mobile fitness applications (MFAs) have entered people's daily lives. However, the extant literature lacks empirical investigations that explore users' continuance usage intentions regarding AI-powered MFAs. To fill this research gap, this paper employs goal-setting theory to establish a research model for exploring how AI-enabled features (i.e. intelligence and anthropomorphism) affect users' perceptions of goal difficulties and goal specificities, which in turn affect their MFA continuance usage intentions.

This paper uses a survey method to analyze the research model, and a total of 223 responses are collected. The partial least squares (PLS) technique is utilized for data analysis.

The results show that intelligence and anthropomorphism affect the continuance usage intention of MFA users through their goal difficulty and specificity. Both intelligence and anthropomorphism positively influence goal specificity, whereas they negatively affect goal difficulty. In addition, goal specificity increases users' MFA continuance usage intention, whereas goal difficulty decreases users' continuance usage intention. The findings of this study provide theoretical contributions for AI technology adoption research and offer practical strategies for firms to retain MFA users.

Based on goal-setting theory, this study reveals that as two primary AI features of contemporary mobile fitness apps, intelligence and anthropomorphism, can increase comprehension of users' perceptions regarding goal difficulty and specificity in the context of users' continuance usage intentions toward AI-powered MFAs.

Software process improvement (SPI) is a knowledge activity that is critical to the excellence of information system development. This study observes two knowledge gaps in the quest for SPI success and proposes a research model that integrates existing knowledge antecedents to address these gaps. Based on organizational learning theory and the dynamic capability view, the proposed model consolidates a firm's absorptive capacity (AC), learning ability in terms of exploration and exploitation and knowledge sharing (KS), and it examines the contextual relationships among these knowledge antecedents on the path to SPI success.

A quantitative research design is implemented to examine the model with a sample of 138 SPI-certified organizations in Taiwan and Mainland China. The partial least squares (PLS) technique is used for the data analysis.

The results reveal the following findings. First, AC triggers the effect of exploration/exploitation on SPI success. Second, KS fosters exploitation but has an insignificant influence on exploration. Third, KS can promote AC, and it serves as the sourcing mechanism for all of the knowledge antecedents. Overall, an integrative set of knowledge learning routes is presented in guiding software firms on the way to SPI success.

In addition to identification of the two knowledge gaps, this study advances the authors’ understanding by comprehending the causal associations of the four knowledge antecedents on the way to SPI success.

Software process tailoring (SPT) is a knowledge- and learning-intensive activity in which a software project team customizes its software development processes to accommodate project particularities. Because SPT critically influences how a project is conducted, SPT performance should be investigated, but the extant literature lacks investigations into how team knowledge mechanisms and team environments contribute to SPT performance. To fill this gap, this study looks into a team's absorptive capacity (AC) and combines a transactive memory system (TMS) and team climate inventory (TCI) to develop a theoretical research model to facilitate the understanding of SPT performance.

This paper is a conceptual study that uses the propositional methodology with a focused review of existing literature pertaining to SPT, AC, TMS and TCI to develop a theoretical model to foster SPT performance. Because this study is conceptually established, further empirical research and studies are also suggested.

The proposed model provides guidance for firms conducting SPT. It also contributes to future research aiming to empirically understand the mechanisms behind the identified team-based knowledge and environmental enablers in the dynamic team learning process that lead to superior SPT performance.

The proposed model provides a fresh look at the dynamic capabilities theory in SPT and innovatively identifies a team's dynamic learning process to show how a team can conduct effective SPT through AC and facilitated by TMS. Environmental climates characterized by vision, participative safety, task orientation and support for innovation act as positive moderators in promoting the team dynamic learning process.

Agile software development (ASD) has emerged as an active research area due to its enormous growth in popularity. The innovative differences between ASD and traditional development include the use of fundamentally different procedures, organizational structures and people, yet organizations still attempt to embrace ASD. Apparently, the underlying factors arousing organizations’ intent to adopt ASD are not well known and have not been well explained in the extant literature. The purpose of this paper is to fill this gap for which the authors propose a conceptual framework based on the business process management (BPM) perspective to identify the environmental stimuli that affect an organization’s ASD adoption.

Proposition for a methodology approach is used to construct a theoretical framework based on existing literature and theories in BPM.

The framework recognizes external and internal environmental stimuli, including institutional isomorphic forces and interior enablers, such as top management championship, the culture type and resource readiness, which affect organizational ASD adoption decisions.

This paper consolidates both the internal and external environmental aspects of the stimuli that lead to ASD adoption and offers insight into creating a suitable context for ASD adoption.

To improve the frequency of adoption of mobile health services (MHSs) by users (consumers), it is critical to understand users' MHS adoption behaviors. However, the literature primarily focuses on MHS adoption-related factors and lacks consideration of the joint impacts of reasons for (RF) and reasons against (RA) on users' attitudes and adoption behaviors regarding MHSs. To fill this gap, this study integrates behavioral reasoning theory (BRT) and protective motivation theory (PMT) to develop a research model by uncovering the reasoning process of personal values, RF and RA, adoption attitudes and behavior toward MHSs. In particular, health consciousness (HC) is selected as the value. Comparative advantage, compatibility and perceived threat severity are considered the RF subconstructs; value barriers, risk barriers and tradition and norm barriers are deemed the RA subconstructs.

A total of 281 responses were collected to examine the model with the partial least squares structural equation modeling (PLS-SEM) method.

The results show that HC positively affects attitude through RA and RF. Additionally, RF partially mediates the relationship between HC and adoption behavior. This study contributes to a deeper understanding of user adoption behavior in MHS and provides practical guidance for the health services industry.

This study contributes to the existing MHS literature by understanding the joint influences of personal values, RF and RA on user attitude, which eventually determines users' adoption decisions regarding MHSs.

Financial technology (Fintech) brings about innovative financial services, such as the possibility of introducing mobile wealth management applications (apps) into consumers' lives. Despite the rapid development of such apps, few studies have focused on users' switching intentions from traditional wealth management services to mobile settings (apps).

Through a survey research method, a total of 378 responses were collected to examine the model. The partial least squares (PLS) technique was employed for data analysis.

To fill this research gap, this paper adopts a push-pull-mooring (PPM) theoretical framework to develop a model for exploring users' switching intentions. According to the empirical results, several push (i.e. perceived inconvenience), pull (i.e. transaction efficiency, perceived personalization and mobile wealth management scenarios) or mooring (i.e. product market expertise and affective commitment) factors are identified that significantly affect switching intention. This study provides theoretical contributions and practical implications for the existing wealth management literature and also offers future research directions.

This study innovatively extends the PPM framework to the traditional and mobile wealth management domains to understand users' switching intentions from offline wealth management services to mobile wealth management apps. The authors uncover several push, pull and mooring factors that are critical for determining users’ switching decisions.

Artificial intelligence (AI) has been widely used as a financial technology (fintech) in the mobile banking (M-banking) domain. However, in the literature, how AI affects users' perceptions of social support and the users' satisfaction and continuance intention (CI) remains unknown. To fill this gap, the two core characteristics of AI, perceived intelligence (PI) and perceived anthropomorphism (PA), are combined with social support theory (SST) (including informational support (IS) and emotional support (ES)) to develop a research model to investigate how PI and PA affect IS and ES, which in turn affect users’ M-banking satisfaction and CI.

This study adopted a random probability sampling method to collect a total of 360 valid responses to verify the proposed model. Partial least squares (PLS) was employed for data analysis.

The results showed that PI and PA both have a significant positive impact on consumers' perception of social support (IS and ES). IS was a direct driver of satisfaction and CI. Surprisingly, although ES was positively associated with satisfaction, the study found that higher levels of ES will decrease CI. This study exposed how AI affects consumers’ satisfaction and CI through SST, and the role of AI in M-banking applications has been further confirmed.

This study expanded the SST to creatively integrate with AI features to reveal the impact of PI and PA on IS and ES, which in turn influence users' M-banking usage.

The development of mobile technology has changed the traditional financial industry and banking sector. While traditional banks have adopted artificial intelligence (AI) techniques to deepen the development of mobile banking applications (apps), the current literature lacks research on the use of AI-based constructs to explore users' mobile banking app adoption intentions. To fill this gap, based on stimulus-organism-response (SOR) theory, two AI feature constructs as stimuli are considered, namely, perceived intelligence and anthropomorphism. This study then develops a research model to investigate how intelligence and anthropomorphism affect task-technology fit (TTF), perceived cost, perceived risk and trust (organism), which in turn influence users' AI mobile banking app adoption (response).

This study used a convenience nonprobability sampling approach; a total of 451 responses were collected to examine the model. The partial least squares technique was utilized for data analysis.

The results show that intelligence and anthropomorphism increase users' willingness to adopt mobile banking apps through TTF and trust. However, higher levels of anthropomorphism enhance users' perceived cost. In addition, both intelligence and anthropomorphism have insignificant effects on perceived risk. The results provide theoretical contributions for AI-based mobile banking app adoption and offer practical guidance for bank planning to use AI to retain users.

Based on SOR theory, this study reveals that as features, AI-enabled intelligence and anthropomorphism help us further understand users' perceptions regarding cost, risk, TTF and trust in the context of AI-enabled app adoption intentions.

Numerous educational applications (APP) have been developed to assist traditional classroom teaching and student learning. APP quality plays a critical role in influencing students' learning behaviors. However, the role negative mindsets, especially computer anxiety, play in how APP quality affects student engagement remains unknown. To address the relationships among APP quality, computer anxiety and student engagement in an APP-based learning environment, we developed an extended information system (IS) success model that includes interface and instructor quality.

To empirically test the proposed model, we conducted a survey with a sample of 225 university students and examined the hypotheses using the partial least squares (PLS) method.

Computer anxiety was demonstrated to fully mediate the relationships between student engagement and interface quality and service quality and system quality. In addition, the instructor quality acts as a partial mediator of the relationship between computer anxiety and student engagement.

This study reveals the important mediating role of computer anxiety in APP-assisted learning and the special status of instructor quality and user experience in influencing student engagement. The findings of this study shed meaningful light on the practical implications for instructors and APP software developers.