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This chapter explains the phenomenon of artificial intelligence (AI) powered by big data in technology and its contribution in knowledge-based marketing in B2B and its impact on rational decision-making in B2B marketing that affects business performance. This chapter is literature review prepared by compiling and reviewing previous literature, studies, articles, books and other sources related to the contribution of big data-enabled AI to B2B marketing. According to the information analysed, the findings show that big data supported by AI plays a significant role in creating user knowledge, external knowledge and customer knowledge, all of which are factors that significantly influence the ability of business-to-business marketers to make rational decisions that affect the performance of their companies. This chapter explains to them the phenomena of AI powered by big data and its effect on B2B marketing rational decision that will enhance company performance and its contribution on knowledge-based marketing in B2B. This chapter contributes to understanding main functions and interactions of AI system powered by big data and how such a system helps in B2B marketing by generating knowledge about customers, users and markets.

This article aims to clarify the concepts used to understand, analyze and improve a patient’s progress through a health service system. A patient pathway describes plans and intentions. Within it, we distinguish between the clinical pathway of decisions and interventions and the care pathway of supportive activities. As a patient pathway is implemented, it turns into a patient journey of what is done, what happens to a patient’s medical condition and what is experienced and felt. We introduce “patient journey disruption” (PJD) as a concept describing the events that need to be prevented from happening to accomplish integrated, coordinated and seamless care.

The method used in this paper is concept analysis. First, an expert steering group worked to refine the concept of PJDs; second, an analysis of similar concepts from related fields was done to root the concept into existing theories, and third, semi-structured interviews with professionals and patients were done to test the concept of PJDs in the home care context.

PJDs are agency-based harmful events in the execution of the care pathway that deviate the patient journey from what can be reasonably expected. PJDs are management failures, which is why they should be studied by healthcare operations management (HOM) and service science scholars with the intention to find ways to prevent them from happening.

This study has limitations, including presenting conceptual ideas and preliminary results that are only indicative.

We believe that the introduction of the concept of PJDs into the literature provides a new, systematic way of approaching the different shortcomings in our healthcare production systems. Moreover, by systematically identifying different PJDs, interventions can be designed and targeted more appropriately.

Managerial challenges regarding healthcare processes have been studied but have not been well defined. The concept of PJDs is an original, well-thought-out definition.

This study examined the factors that affect attitudes and intentions for sustainable adoption of mobile financial services (MFS) in Nigeria.

The study expands the Technology Acceptance Model (TAM) by incorporating constructs like perceived service quality, perceived ease of use, perceived usefulness, perceived credibility, perceived trust and attitude. It includes an empirical analysis with 382 participants and qualitative insights from semi-structured interviews to investigate the challenges and opportunities associated with MFS adoption in Nigeria.

The findings show that perceived service quality, perceived usefulness and attitude positively influence the adoption of MFS. However, perceived ease of use and perceived credibility have little impact on adoption. Qualitative insights from Study 2 shed light on the challenges and opportunities as well as the reasons behind the insignificant effects of perceived ease of use and perceived credibility.

This research stands out by using a mixed-methods approach, blending quantitative and qualitative analysis to provide a more detailed understanding of the factors influencing MFS adoption.

This study used post-occupancy evaluation (POE) to assess the performance and effectiveness of student housing by examining occupants’ satisfaction with the facility across three performance elements: technical, functional and behavioral. This study aims to address a significant gap in the existing research concerning the POE of university student housing facilities, particularly in understanding how well these facilities fulfill occupant needs across the aforementioned three elements.

This study assesses the existing literature, examines the dormitory’s physical parameters through walkthrough inspections and measures occupant satisfaction through surveys and focus group sessions. The study analyzed questionnaire responses using a four-point Likert scale, using Microsoft Excel software to determine the weighted average response for each performance element.

The analysis indicated that students were satisfied with most housing condition parameters. However, noise management, lighting control, air circulation, washroom facilities, cleanliness, power sockets for equipment and several study rooms and furnishings require improvement to enhance student well-being and performance.

This study provides significant information to aid in making informative decisions on building maintenance, retrofitting and facility upgrading. It also contributes to enhancing the field’s knowledge about POE in student housing facilities. It emphasizes the importance of using physical building attributes and user-centric features to fulfill students’ needs and expectations regarding facilities.