Journal of Information Technology Management (مدیریت فناوری اطلاعات)

The microlearning approach is increasingly adopted in organizational training because it delivers educational content in concise and easily digestible segments. This approach is widely viewed as both engaging and effective. However, empirical evidence regarding its effectiveness remains limited, particularly when microlearning is a prerequisite or a post-requisite to conventional training courses. To address this gap, the present study evaluated the effectiveness of prerequisite and post-requisite microlearning formats compared to traditional training methods in enhancing employees’ professional competencies. This study employed a quasi-experimental post-test design with a control group. The target population comprised employees of a state-owned bank in Tehran Province. From this population, 90 individuals were selected through convenience sampling and randomly assigned to three groups: a prerequisite microlearning group (experimental), a post-requisite microlearning group (experimental), and a traditional training group (control). All groups received a training course titled Problem-Solving in the Banking Industry. For the experimental groups, the course was delivered using a blended approach that combined microlearning with face-to-face instruction. In contrast, the control group received the training exclusively through face-to-face sessions. Data collection and analysis were conducted over three weeks using the Kirkpatrick Evaluation Model. The findings revealed that the experimental groups reported significantly higher levels of reaction (p = 0.017) and learning (p = 0.001) compared to the control group. However, no significant difference in behavioral change was observed among the groups (p = 0.115). These results suggest that while microlearning can enhance learner reactions and learning outcomes, it may not be sufficient to drive behavioral change in the workplace.

Blended learning is a pedagogical approach that combines face-to-face instruction with online activities and has garnered significant interest in recent years. Despite the potential benefits of blended learning, it faces several critical issues that may dampen stakeholders' enthusiasm within universities. Consequently, the current study explores the key challenges of blended learning in higher education institutions. The data for this research were collected through a qualitative approach, using a descriptive phenomenological method and semi-structured interviews with experts in the field. The findings were then analyzed using Colaizzi’s (1978) seven-step method. During our research, interviews were conducted with 14 experts in the field through purposeful sampling. From these comprehensive discussions, a total of 112 significant statements were identified. These statements were then meticulously categorized into ten initial themes, providing a structured overview of the data. Further analysis allowed us to distill the challenges associated with the blended learning approach in higher education into three critical factors. The validity of the qualitative data, based on the four criteria of Lincoln and Guba (1985)—credibility, transferability, dependability, and confirmability—was examined through re-coding by two independent coders and confirmed. The findings reveal that the challenges associated with implementing blended learning in higher education can be categorized into personal, organizational, and support-related factors. Each of these dimensions encompasses various critical elements. Notably, these research outcomes hold significant potential for facilitating the successful adoption of a pragmatic blended teaching and learning approach within higher education.

Extensive technological advancements have highlighted the importance of digital transformation in improving business performance. While prior research on this topic has been done in the information systems and business management domains, it has been limited to specific areas. Therefore, it is crucial to evaluate the impact of digital transformation comprehensively. This research aims to systematically identify critical themes, significant topics, main concepts, and trend priorities. The study involved the analysis of 474 research papers from 2015 to 2024 from reputable databases such as SCOPUS, Web of Science, and IEEE Xplore. First, thematic analysis identified the main themes and interpreted their relationships. Identified themes refer to technological changes at the operational and strategic levels through data analytics, digitalization, collaborative learning, and digital interaction. Realizing that digital transformation leads to value creation, improved service quality, customer experience, and long-term communication in digital ecosystems. These findings were related to dynamic capability theory concepts and compared with theory constructs like sensing, seizing, and transforming. Next, text mining techniques were used for deeper investigation, including word cloud, topic modeling (Latent Dirichlet Allocation), and text clustering (K-means). Findings were categorized into three perspectives: business, customer, and systemic, highlighting the influential role of digital technologies, particularly artificial intelligence (AI) capabilities. Moreover, trend analysis presented research priorities using VOSviewer. Finally, research innovation involved designing thematic networks and examining the relevance of significant topics as a research artifact with subtle differences compared to the conducted research. This novel approach provides five targeted propositions to audiences for future research.

The challenge of allocating marketing budgets across multiple online channels is a significant issue for practitioners and continues to be a compelling area of research within the academic community. Many practitioners attribute credit to touchpoints in analyzing online users’ journeys based on intuition or by comparing existing models. Touchpoints are the interaction moments between companies and customers. Marketers monitor all data related to touchpoints throughout the customer journey and attempt to assess the impact of each advertising channel. Understanding each touchpoint is crucial for making decisions about budget allocations and setting inventory prices. Numerous studies have been conducted to categorize and analyze touchpoints. However, a detailed and comprehensive study on this topic is lacking. In this study, nine semi-structured interviews were conducted with experts and academics in the field, leading to the identification of 35 distinct touchpoint features. The features were extracted using MAXQDA software and a thematic analysis methodology. These features have been organized into five main categories: Time (9 features), Technology (6 features), Marketing (7 features), Visits (7 features), and Events (6 features). Utilizing these features allows for detailed monitoring of online user behavior, and by integrating them into attribution models, it becomes possible to make accurate predictions about conversions.

The banking industry is undergoing a significant transformation driven by digital technologies, evolving customer behaviors, and increasing regulatory pressures. To remain competitive, banks must adopt governance frameworks that integrate digital innovations to enhance operational efficiency and improve environmental, social, and governance (ESG) performance. This study identifies governance framework archetypes essential to digital transformation in banks through a comprehensive research methodology, including a literature review of digital governance frameworks, a comparative analysis of 11 leading digital banks worldwide, and latent class analysis to uncover key archetypes. Our findings reveal nine distinct governance archetypes, categorized into three dimensions: structural, including Centralized, Semi-centralized, and Open Innovation-oriented banks; dedicated processes, comprising Continuous Improvement, Vanguard, and Fast Follower banks; and relational mechanisms, featuring Self-empowering, Explorer, and Relationship-oriented banks. This classification advances the understanding of governance approaches that effectively support banks in their digital transformation journeys. The implications of these archetypes are substantial, offering a framework for banks to align their strategies with digital transformation initiatives. By adopting these governance structures, banks can better navigate the complexities of the digital landscape, foster innovation, and ultimately enhance their service offerings while addressing the evolving demands of customers. This research contributes to the growing body of knowledge on digital governance in banking and provides guidance for financial institutions striving to succeed in an increasingly digital world.

In the digital economy era, the widespread use of smartphones has brought about new information security threats, increasing the risk of data leakage from personal devices. Digital literacy, defined as the skills and knowledge needed to navigate digital life effectively, offers new perspectives and motivation for safeguarding personal information security. This study investigates the relationship between digital literacy and smartphone users’ intention to protect their information security. Drawing on Protection Motivation Theory (PMT) and Technology Threat Avoidance Theory (TTAT), a theoretical model was developed to examine both the direct and indirect effects of digital literacy on users’ information security protection intentions. Questionnaire data from 372 smartphone users in China were analyzed using Structural Equation Modeling (SEM). The results reveal that digital literacy has a significant positive impact on users’ response efficacy, self-efficacy, and their intention to protect information security. Moreover, digital literacy influences protection intention indirectly through self-efficacy and response efficacy. However, perceived threat, although positively influenced by digital literacy, does not have a significant effect on users’ protection intention. This study offers valuable insights for policymakers, educators, and businesses in promoting a secure mobile environment and provides practical recommendations for enhancing personal information security in the digital age.

Many Information Systems (IS) projects experience serious problems that prevent them from meeting schedule, budget, and functionality targets. Managers often escalate their commitment to such projects, plowing ahead with them instead of hitting the pause button to address issues, a process known as project escalation. Due to the increasing pressure to develop systems and bring products to market faster, making decisions that involve time are more important than ever. While time has been studied in the IS domain, the effect of emphasizing time in a project’s name on IS project escalation decisions is not known. In this study, we explore whether a project name that explicitly refers to time can influence escalation decisions, and we examine the underlying mechanism through which that occurs. Sixty-two practitioners participated in a 2x1 factorial design experiment in which the project name was manipulated, but all other project information was identical. We theorize that emphasizing time in the project name can cause selective perception, drawing attention towards the schedule of the project and away from other aspects. Such selective perception can increase the likelihood of escalation of commitment to the schedule of the project when facing quality issues that require deviating from this schedule. We hypothesize that this effect of selective perception on escalation can be both direct and indirect. The results from the experiment support our research model.