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This chapter delves into the specific heuristics, biases, and cognitive errors that often arise during decision-making processes in healthcare. It explores how specific mental shortcuts can lead to inconsistencies and irrationalities. Key concepts include statistical evaluation errors, such as the base rate fallacy and the law of large numbers, and causal inference issues like regression to the mean and omitted variables. This chapter also covers common cognitive biases, such as confirmation bias, optimism bias, action bias, halo effect, overdiagnosis, etc., which influence medical professionals and patients in interpreting information and deciding. Recognition of such biases can enhance medical decision outcomes as well as improving the communication between stakeholders.

Adoption of Clinical Decision Support Systems (CDSS) is a crucial step towards the digital transition of the healthcare sector. This review aims to determine and synthesise the influential factors in CDSS adoption in inpatient healthcare settings in order to grasp an understanding of the phenomenon and identify future research gaps.

A systematic literature search of five databases (Medline, EMBASE, PsycINFO, Web of Science and Scopus) was conducted between January 2010 and June 2023. The search strategy was a combination of the following keywords and their synonyms: clinical decision support, hospital or secondary care and influential factors. The quality of studies was evaluated against a 40-point rating scale.

Thirteen papers were systematically reviewed and synthesised and deductively classified into three main constructs of the Technology–Organisation–Environment theory. Scarcity of papers investigating CDSS adoption and its challenges, especially in developing countries, was evident.

This study offers a summative account of challenges in the CDSS procurement process. Strategies to help adopters proactively address the challenges are: (1) Hospital leaders need a clear digital strategy aligned with stakeholders' consensus; (2) Developing modular IT solutions and conducting situational analysis to achieve IT goals; and (3) Government policies, accreditation standards and procurement guidelines play a crucial role in navigating the complex CDSS market.

To the best of the authors’ knowledge, this is the first review to address the adoption and procurement of CDSS. Previous literature only addressed challenges and facilitators within the implementation and post-implementation stages. This study focuses on the firm-level adoption phase of CDSS technology with a theory refining lens.

Previous studies have identified concerns and anxiety in individuals who are without their mobile phones, which is known as nomophobia, an acronym for “no mobile phone phobia.” However, there is currently limited evidence of qualitative research that explores nomophobia. The purpose of this study is to explore personal experiences and individual meanings associated with mobile phone use and nomophobia.

To address this gap, the present study employed a Heideggerian phenomenological approach to investigate the issue. Ten college students, who have medium to high nomophobia were selected as respondents. Semi-structured interviews were conducted to collect data, which were then transcribed verbatim and analyzed using reflexive thematic analysis.

A deep understanding of the psychological dynamics, experiences, meanings, perceptions and beliefs of individuals regarding smartphone use can only be explored through a qualitative approach that presents personal statements of individuals through in-depth semi-structured interviews. This study contributes to a deep understanding of the psychological dynamic of nomophobia.

This study has limitations that must be carefully considered. First, the respondents came from a university with a sample size of 10 people, which may not fully represent the phenomenon of nomophobia among students due to differences in cultural and academic backgrounds. However, we addressed this limitation by selecting only students who scored moderate to high levels of nomophobia. Second, the researchers acknowledge that the sample used in the study may not be fully representative of the broader target population or a larger group, as previously mentioned. Therefore, generalizing the findings of this research must be done carefully, being cautious and thoughtful to avoid hasty conclusions.

In the functional context, it is recommended for individuals to be more mindful of their smartphone usage and strive to strike a balance between utilizing their device's capabilities for productive purposes and avoiding excessive dependency that may lead to distractions or information overload. This includes limiting excessive smartphone usage for entertainment purposes, restricting aimless and irrelevant Internet browsing and implementing effective time management when using smartphones. For smartphone users from the ontological context, the advice is to critically evaluate their digital presence and ensure that their online activities align with their true values and self-perception, promoting responsible and ethical smartphone use. Engaging in fasting or break sessions by completely turning off the smartphone at specific times and utilizing that time for activities such as reading books, writing and engaging in spiritual practices, or exercising is also advisable. In the anthropomorphic context, individuals are advised to reflect on the potential emotional dependence on their smartphones and consider establishing healthy boundaries to avoid excessive reliance on these devices to fulfill emotional needs. One practical recommendation is to engage in self-reflection, where individuals take some time to ponder their smartphone usage patterns and emotional attachment to the device. They should ask themselves why they feel the need to constantly check their phone and how it impacts their emotions and overall well-being.

This study contributes to a deep understanding of the psychological dynamics of nomophobia by exploring the experiences, meanings, perceptions, and beliefs of individuals regarding smartphone use.

Visualizing relations of textual data requires dimension reduction to increase the interpretability of output. However, traditional dimension reduction methods have some limitations, such as the loss of feature information during extraction or projection in dimension reduction and uncertain results due to the mixture of word labels. In this study, we develop the textual data visualization algorithm using statistical methods to present statistical inferences on the data. We also construct the algorithm in a way that the user can analyze textual data easily.

Unstructured data, such as textual data, is sensitive to choosing analysis methods. In addition, textual data is generally large-sized and sparse. Considering such characteristics, we applied latent Dirichlet allocation to separate data to minimize the loss of information, and false discover rate (FDR) control to reduce dimension in a statistical way.

The relation of textual data can be derived in a one-click way, and the output can be interpreted without background information, with separated topics.

The algorithm is constructed based on the Korean language. However, any language can be used without linguistic information. This study can be an example of usage and flow, which using not well-known dimension reduction methods can replace traditional methods.

Data transformation has prompted enterprises to rethink their strategic development. Scholars have frequently acknowledged the vast potential value of supply chain data and realised that simply owning data resources cannot guarantee excellent innovation performance (IP). Therefore, this study focussed on the mediating and moderating issues between data-driven supply chain orientation (DDSCO) and IP. More specifically, the purpose was to explore (1) whether DDSCO promotes enterprise innovation through dynamic and improvisational capabilities and (2) how information complexity (INC) plays a moderating role between capabilities and performance.

An empirical study was performed using the results of a questionnaire survey, and a literature review was used to build the premises of this study. A sample was conducted on 296 Chinese enterprises, and the data collected were used to test the hypothesis by successive regression.

This research has implications for the theoretical development of DDSCO, as well as the dynamic capabilities (DC) and improvisation capabilities (IC) in innovation strategic literature. The empirical results show that DDSCO has a direct, positive impact on both DC and IC, which thus positively impact IP. Meanwhile, IC has a negative moderating effect on the path joining DC and IP. Conversely, IC has a positive moderating effect on the path joining IC and IP.

Although this study has limitations, it also creates opportunities for future research. The survey comes from different industries, so the possibility of unique influences within industries cannot be ruled out. Second, the authors' survey is based on cross-sectional data, which allow for more comprehensive data verification in the future. Third, this study also provides opportunities for future research, because it proves that DC and IC, as partial mediators of DDSCO and IP, can mine other paths of the data-driven supply chain in IP. For example, the perspective of the relationship between supply chain members, knowledge perspective, etc.

The research findings offer a novel perspective for enterprise managers. First, enterprises can leverage supply chain data to gain competitive advantages in innovation. Second, it is imperative for enterprises to acknowledge the significance of developing dynamic and IC. This also requires enterprises to acknowledge innovations in DDSCO necessitate a focus on dynamic and IC. Third, it is recommended that managers take into account both sides of IC and encourage enterprises to prioritise the utilisation of IC.

Empirical research results revealed how DDSCO improves IP and is an extension of digital transformation in the supply chain field, providing new opportunities and challenges for enterprise innovation. It can also expand the enterprise's understanding of DDSCO. Second, based on resource-based theory, it is possible to develop and test theoretical arguments regarding the importance of dynamic and IC as intermediaries in the DDSCO-IP. Third, the authors conducted simulations of highly dynamic data environments to develop and test theoretical arguments about the importance of IC as a moderator of capabilities-performance relationships.