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Investor perception analysis on priority benefits of corporate income tax incentives in Indonesia
Published in Siska Noviaristanti, Contemporary Research on Management and Business, 2023
In the decision-making process, management is faced with alternatives in solving problems. Management is often faced with problems that are comprehensive and cannot be compared between one option and another. AHP is a flexible and capable method in the decision-making process either for determining priorities, comparing alternatives, and making the best decisions, taking into account qualitative and quantitative aspects under certain conditions (Saaty 1990). The AHP computed the weights of criteria and sub-criteria. The factors were pairwise compared using a predefined scale (Saaty 1990). Further, the same scale was used to assign weights for ranking the alternatives. After pairwise comparison among nine criteria, a (9 x 9) dimension matrix was formed in which each component represented the weight of the criterion given by the respondent. Further, the mathematical computation was carried out to establish the relative weight of the criteria.
Swarm Intelligent Techniques for Cloud Service Provider Selection in a Multi-cloud Environment
Published in Indrajit Pan, Mohamed Abd Elaziz, Siddhartha Bhattacharyya, Swarm Intelligence for Cloud Computing, 2020
Amany M. Mohamed, Hisham M. Abdelsalam
As a result of the continually increasing number of cloud service provider’s evaluation criteria, research papers depended on user experience and preferences to select the best cloud service provider. Analytic Hierarchy Process (AHP) was the most used method to rank cloud providers [4,5,8–10,14,15]. AHP is a flexible and powerful tool for dealing with complex decision-making. It depends on three principles: (1) decomposition of the problem, (2) comparative judgment of the elements, and (3) synthesis of the priorities. However, when a large number of criteria is considered, applying AHP becomes time-consuming. Another weighted methods were used to solve the provider selection problem. Baranwal and Vidyarthi [16] and Shirur and Swamy [17] proposed Ranked Voting Method, while Upadhyay [18] proposed Technique of Order Preference by Similarity to Ideal Solution (TOPSIS).
Data Analysis
Published in Shyama Prasad Mukherjee, A Guide to Research Methodology, 2019
AHP generates a weight for each evaluation criterion based on the decision-maker’s pair-wise comparison among the criteria to get over the problem that no alternative may be found the ‘best’ according to all the criteria. A higher weight implies a greater importance for the criterion in making overall prioritization. Next, for a fixed criterion, AHP assigns a score to each alternative according to the decision-maker’s pair-wise comparison among the alternatives based on that criterion. Finally, AHP combines the scores for the alternatives and the criteria weights. A final prioritization of the alternatives is in terms of the weighted total of score for each. The pair-wise comparisons which form the bedrock of AHP are somewhat analogous to Thurstone’s product scaling, though the latter does involve several judges or decision-makers stating their preferences for one product or alternatives compared to the a second where the two are presented as a pair. Moreover, Thurstone’s method does not involve multiple criteria.
Mediating governance goals with patients and nurses satisfaction: a multi-actor multi-objective problem including fairness
Published in International Journal of Production Research, 2023
Valentina Bonomi, Renata Mansini, Roberto Zanotti
Scoring methods are heuristic algorithms commonly employed for solving combinatorial optimisation problems, particularly those that involve selecting items. They provide a streamlined decision-making process that facilitates the comparison and evaluation of different alternatives. There are several scoring methods in the literature to handle multi-criteria selection. The Analytic Hierarchy Process (AHP) and its variants (Ishizaka, Pearman, and Nemery 2012; Saaty 1990; Saaty and Vargas 2013), such as the Analytic Network Process (ANP) and AHPSort, are commonly used. AHP is a method for prioritising and weighting decision criteria by breaking down complex decisions into a hierarchy of smaller, more manageable sub-decisions. AHP uses a pairwise comparison matrix to determine the relative importance of each criterion with respect to the others. ANP extends the AHP by allowing for interdependent criteria and decision elements to be represented as a network, rather than a hierarchy. Another method is the Elimination by Aspects (EbA) (Tversky 1972), which involves eliminating alternatives that fail to meet a minimum threshold for each criterion. EbA is useful when decision-makers have strict minimum requirements for each criterion. In multi-actor multi-objective problems, similar ideas can be found, as shown in Sirikijpanichkul, Winyoopadit, and Jenpanitsub (2017), where the authors present a scoring method that requires a predefined order or weight from each stakeholder.
The assessment of factors influencing Big data adoption and firm performance: Evidences from emerging economy
Published in Enterprise Information Systems, 2023
Mahak Sharma, Ruchita Gupta, Rajat Sehrawat, Karuna Jain, Amandeep Dhir
The AHP rankings are the best way that allows prospective adopters to understand the offerings of big data. AHP scores assess the strength of alternative choices relative to the best ones. The results thus help policy and decision-makers to understand the potential of BDA to improve a firm’s performance. For big data service providers, the present study recommends building trust with all big data stakeholders. Providers can also differentiate among prospective big data users based on the determinants recognised in this study. Big data quality and predictive analytics accuracy are critical determinants in a firm’s efforts to generate greater business benefits. Tourism and hospitality firms are advised to develop strategic procedures that rely on the significance of the adoption determinants and their interrelationships while choosing a suitable big data service provider. Meanwhile, government bodies are encouraged to establish proper policies and measures to foster trust in and loyalty to hospitality firms. Although a few factors are more critical than others, management and strategy decisions should consider all factors (Behl et al. 2019). It may also be essential to allocate separate teams to explore each perspective’s working strategies. Thus, we recommend that service providers offer well-recognised and trusted services with suitable attributes after judicious consideration of the highest ranking factors under each category.
Evaluation of the quality of health and safety services with SERVPERF and multi-attribute decision-making methods
Published in International Journal of Occupational Safety and Ergonomics, 2022
Selçuk Alp, Fatih Yilmaz, Ebru Geçici
Taking human judgment into consideration in decision processes can directly affect the effectiveness and form of the decision. One of the methods used in decision-making situations is the AHP. This is a multi-attribute decision-making (MADM) method developed by Saaty [34] for the solution of complex problems and is applied in many areas. The AHP is a method that lists decision options (alternatives) in order of importance within the framework of determined criteria. This method is based on binary comparisons inherent in human nature. The AHP method evaluates how important, preferred or dominant the alternatives and criteria are compared to each other with paired comparisons. The scale presented in Table 2 is generally used when making binary comparisons.