Hybrid Analysis of the Decision-Making Factors for Software Upgrade Based on the Integration of AHP and DEMATEL

Software is a very important part to implement advanced information systems, such as AI and IoT based on the latest hardware equipment of the fourth Industrial Revolution. In particular, decision making for software upgrade is one of the essential processes that can solve problems for upgrading the information systems. However, most of the decision-making studies for this purpose have been conducted only from the perspective of the IT professional and management position. Moreover, software upgrade can be influenced by various layers of decision makers, so further research is needed. Therefore, it is necessary to conduct research on what factors are required and affect the decision making of software upgrade at various layers of organization. For this purpose, decision factors of software upgrade are identified by literature review in this study. Additionally, the priority, degree of influence and relationship between the factors are analyzed by using the AHP and DEMATEL techniques at the organizational level of users, managers and IT professionals. The results show that the priority, weight value, causal relationship of decision factors of users, managers and IT professionals who constitute the organizational level were very different. The managers first considered the benefits, such as ROI, for organization as a leader. The users tended to consider their work efficiency and changes due to the software upgrade first. Finally, the IT professionals considered ROI, budget and compatibility for the aspect of the managers and users. Therefore, the related information of each organizational level can be presented more clearly for the systematic and symmetrical decision making of software upgrade based on the results of this study.

The Analysis of Decision-making Items for Operation Management of Digital Twin Simulators for Sewage and Water Treatment Facilities

This paper addresses the derivation of decision-making factors for the operation and management of the Cyber Physical systems (CPS)-linked wastewater treatment plants (WWTPs) and drinking water treatment plants (DWTPs) simulator. The analytical hierarchy process (AHP) method was applied to evaluate the importance of each influencing factor on the operational elements targeting experts. Here, the experts were 37 people working for WWTPs and 30 people working for DWTPs, respectively. The analysis factors for decision-making were influent load, reactor capacity, treatment process, occurrence of high turbidity influent, risk, urgency, response, and recovery, and their relative importance was analyzed. Among the operational elements of WWTPs, influent fluctuations have been shown as the most important factor. Conversely, the possibility of occurrence was found to be the most important influencing factor. In the case of DWTPs, the inflow of high turbidity was found to be the main operating factor, and the influencing factors were the probability of occurrence and the degree of risk. Based upon the results obtained, this study is expected to contribute to the establishment of a stable system of both WWTPs and DWTPS by identifying influent fluctuations, which are a major influencing factor, and by controlling operation factors connected with the establishment of a digital twin simulation.

DECISION-MAKING FACTORS IN CONSUMER BEHAVIOUR ON THE MARKET WITH DECORATIVE COSMETICS

The article explores major decision-making factors in consumer behaviour when purchasing decorative cosmetics. The employed methods involve brainstorming and structured interviews. The most powerful internal stimuli are body care and looking good. On the other hand, a desire to try a new cosmetic product plays a rather subordinate role. The main external purchasing factors involve a recommendation from a friend or relative. On the contrary, aspects such as vegan composition of the product or its packaging do not attract much attention. However, research conclusions cannot apply on the long-term basis given to the rapid development of new technologies and marketing strategies in this branch. It is therefore imperative to monitor the current market trends.

Where to Retire? Experiences of Older African Immigrants in the United States

The needs and conceptualization of age-friendliness likely vary for immigrant older adults compared to native-born older adults. For example, Hispanic immigrant older adults often return to their home country following the development of ill health. Doubling in size since the 1970’s, the aging needs of African immigrants are not fully understood. This qualitative study examined experiences of aging and retirement planning for African immigrant older adults in the United States (U.S.). Specifically, it explored the factors, processes, and ultimate decision of where these older adults planned to retire. We analyzed semi-structured interviews with 15 older African immigrants in the Baltimore-Washington Metropolitan area. Data were analyzed using thematic analyses in NVivo. The majority of participants were women, with a mean age of 64. We identified three overarching themes with ten sub-themes. The themes included: 1) cultural identity: indicating participant’s comfort with the U.S. society and culture; 2) decision making: factors that impact participants' choice of retirement location, and 3) decision made: the final choice of where participants would like to retire. Age-friendliness for immigrant older adults in the U.S. is complex and it includes the traditional domains such as physical and sociocultural environment (e.g. housing, transportation, and income). However, immigrant age-friendliness also needs to include wider contextual aspects such as political climate in their country of origin, immigrant status, family responsibilities, and acculturation in the U.S. More research is needed understand and facilitate age-friendly environments for transnational immigrant older adults.

Maturity Models and Sustainable Indicators—A New Relationship

This study aims to investigate the relationship between maturity models adopted by information technology companies and the sustainability indicators that are currently considered decision-making factors for investors and customers. The research is based on previous studies, Control Objectives for Information and Related Technology (COBIT), and Global Reporting Initiative (GRI) standards, and indicators of the Sustainable Development Goals (SDG) defined in 2015 by the United Nations. As a result of the intersection between the GRI and SDG indicators with COBIT requirements, a set of 50 indicators covering four dimensions of sustainability was identified. In the environmental dimension, 11 indicators were identified, in the economic dimension six indicators, in social dimension 14 indicators, and, at last, in the governance dimension, there were 19 convergent indicators between COBIT and GRI. This set of 50 proposed indicators was validated by analyzing the content of the sustainability reports available on the websites of information technology companies, making it possible to relate the sustainable practices and strategies adopted by such companies with the indicators suggested in this study. Furthermore, we identified that the SDGs are incorporated into the strategic objectives of seven of the nine companies analyzed.

INNV-13. UNDERSTANDING FACTORS THAT INFLUENCE THE DECISION OF ACCEPTING TUMOR TREATING FIELDS (TTF) THERAPY

BACKGROUND Tumor Treating Fields (TTF) Therapy is an FDA-approved therapy in the first line and recurrent setting for glioblastoma. Despite Phase 3 evidence showing improved survival, it is not uniformly utilized despite its availability. This qualitative prospective study interviewed glioblastoma patients to better understand key driving factors for decision making. METHODS Adult glioblastoma patients who were offered TTF and who signed IRB approved consent were included. Patients participated in a one-time recorded interview with the researchers from the Northwestern University Department of Medical Social Sciences and were asked about factors shaping their decision to use or not use TTF. RESULTS 40 patients were enrolled with a mean age of 53 years, 92.5% were white and 60% were male. Of the 33 (82.5%) participants who accepted TTF, 23 (69.7%) reported their physician recommending TTF, 8 (24.2%) reported physician neutrality toward TTF, and 2 (6.1%) said their physician advised against TTF. Among the 7 (17.5%) participants who did not choose TTF, 4 (57.1%) reported physician neutrality, 2 (28.6%) reported that their physician advised against TTF, and 1 (14.3%) reported that their physician recommended TTF. Participants who decided against TTF stated that head shaving, appearing sick, and inconvenience of wearing/carrying the device most influenced their decision. For those choosing to use TTF, the most influential factors were extending life and following their doctor's opinion; other factors included level of familial support and the clinical evidence supporting TTF. DISCUSSION This clinical study was a collaboration with the Medical Social Sciences team to better understand the key factors that drive patient decision making with TTF. Findings suggest that physician support and positive Phase 3 results are among the key decision-making factors. Properly understanding the path to patients’ decision making is crucial in optimizing use of TTF and other therapeutic decisions for glioblastoma patients.

Four-pronged decision support framework for implementing industrialized construction projects

Purpose Industrialized construction (IC) is promoted to address some of the ills associated with the processes and products of the traditional construction approach. With several successful projects, IC is progressively becoming a preferred alternative construction approach and spurred the interest of contractors, developers and housing authorities in the technology. Increasingly, these stakeholders are keen to ascertain the compatibility and feasibility of using IC in their projects. This paper aims to develop a knowledge-based decision support framework for implementing industrialized construction projects (ICPs) that can facilitate better and informed decision-making when deciding to implement ICPs. Design/methodology/approach A comprehensive literature review was implemented to recruit 40 decision support factors (DSFs) and grouped into project requirements, location and site attribute, labour considerations and organizational factors. A 3-member expert panel validated the relevance of 35 DSFs, which became candidates for a structured questionnaire survey of experts in 18 countries. Statistical techniques are used to evaluate and prioritize the DSFs, leading to the development of a conceptual framework. Findings Statistical analysis revealed 33 significant DSFs. The top five most significant factors that could influence the decision to implement IC in a project include a stringent requirement for project quality control, suitability of the design for IC, organizational readiness and competencies in ICPs, client receptivity to IC and the need to minimize field construction time. A framework of project requirements, location and site attributes, labour considerations and organizational factors was proposed as decision support. Practical implications The proposed framework may help to inform decision-making regarding the implementation of IC in a project. It has wider applicability because it includes technical, managerial and operational aspects of and the required competencies for IC, which are shared between project types and territories. The prioritized DSFs could be used as a guide when implementing IC, especially in countries where bespoke decision support systems cannot be developed. Originality/value The paper delineated the most important DSFs that are shared between IC project types and territories and can be used to investigate the compatibility of using IC in a proposed project. This research constitutes the first exclusive attempt at delineating, quantifying and ranking the sets of decision-making factors, drawing on international data set and contributes to the empirical checklist of DSFs for ICPs.

Constrained Optimization Based on Hybridized Version of Superiority of Feasibility Solution Strategy

Teaching learning based optimization (TLBO) is a stochastic algorithm which was first proposed for unconstrained optimization problems. It is population based, nature-inspired, and meta-heuristic that imitates teaching learning process. It has two phases, teacher and learner. In teacher phase, the teacher who is well-learned person transfers his/her knowledge to the learners to raise their grades/results; while in learner phase, learners/pupils learn and refine their knowledge through mutual interconnection. To solve constrained optimization problems (COPs) through TLBO we need to merge it with some constraint handling technique (CHT). Superiority of feasibility (SF) is a concept for making CHTs, existed in different forms based on various decisive factors. Most commonly used decision making factors in SF are number of constraints violated (NCV) and weighted mean (WM) values for comparing solutions. In this work, SF based on number of constraints violated (NCVSF) and weighted mean (WMSF) are incorporated in the framework of TLBO. These are tested upon CEC-2006 constrained suit with the remark that single factor used for the decision making of winner is not a wise idea. Mentioned remark leads us to made a single CHT that carries the capabilities of both discussed CHTs. It laid the foundation of hybrid superiority of feasiblity (HSF); where NCV and WM factors are combined with giving dominance to NCV over WM. In current research three constrained versions of TLBO are formulated by the name NCVSF-TLBO, WMSF-TLBO, and HSF-TLBO; while implanting NCVSF, WMSF, and HSF in the framework of TLBO, respectively. These constrained versions of TLBO are evaluated on CEC-2006 with the remarks that HSF-TLBO got prominent and flourishing status among these.