Evaluating Appointment of Division Managers Using Fuzzy Multiple Attribute Decision Making

Abstract

Subsidiaries typically start out as a company division. As the company expands its product lines, the regions it operates in, or the customers it serves, the company is likely to combine the related research and development, procurement, production, and sales departments into a relatively discrete organizational structure. As such, the head of the division is often of equal importance as the company president. In particular, when the product has a competitive advantage, the head of the division has more authority in the company’s future operational planning. Thus, when a company has a multidivisional organizational structure, the heads of those divisions typically have considerable responsibilities. In this study, literature data were combined with a fuzzy Delphi expert questionnaire survey to determine the constructs and criteria for assessing candidates for division manager. Subsequently, the fuzzy decision-making trial and evaluation laboratory (DEMATEL) and the fuzzy DEMATEL-based analytic network process were used to identify the causal relationships between criteria and their weights, and the fuzzy technique for the order of preference by similarity to ideal solution was used to rank the solutions to approximate the company’s optimal candidate for division manager and provide the ideal decision-making solutions, which may offer companies with the reference of selecting the senior executives.

Evaluating E-Teaching Adoption Criteria for Indian Educational Organizations Using Fuzzy Delphi-TOPSIS Approach

“…In Phase 2, the Fuzzy Delphi method (FDM) was employed in the initial list of sub-criteria in order to select the most relevant ones and to finalize the criteria following the distribution of a questionnaire to educational institution respondents in India. FDM was used to obtain a collective conclusion by reducing the fuzziness of expert judgments, which improved the usefulness and reliability of questionnaires [46]. In addition, FDM can reduce sample size and research time, and offer a clearer expression of the decision makers knowledge.…”

“…This study focused on the four criteria for e-teaching adoption by EOs. However, in the present literature, Chen et al [46] weighed the criteria for assessing candidates for division manager using less than ten responders, whereas Sagnak et al [47] analyzed sustainable collection and center location selection using around 30 inputs from the industry. In addition, Gupta [48] noted the major advantage of using TOPSIS was the requirement of less data points from experts such as criteria weights and linguistic preference of alternatives.…”

Enhancing Capacity Building Prior to Appointment as Heads of Departments in Universities

“…To ensure high-quality education and the efficient functioning of departments, the Head of the Department shoulders the pivotal responsibility of supervising, directing, organizing, and evaluating both the department's activities and its faculty members. Achieving this mandate necessitates adept management strategies, efficient resource allocation, and the requisite knowledge and experience to execute the university's objectives as the department's primary policy executor and public face (Chen et al, 2021;Owens, 2014).…”

“…The appointment of a Head of Department is a significant decision made by the Vice-Chancellor based on the recommendations of the Provost and the Dean of the Universities. If a professorial member of the department is unavailable, the next category of senior members, such as Senior Lecturers or Senior Research Fellows of the Research units, are typically selected to assume the position (Chen et al, 2021). If a Lecturer is ever chosen, they serve on an interim basis as coordinators.…”

Fuzzy Discretization on the Multinomial Naïve Bayes Method for Modeling Multiclass Classification of Corn Plant Diseases and Pests

“…Discretization is a preprocessing technique to improve the knowledge extraction process of continuous-type data and is also helpful for improving the model [1][2][3]. This process is essential in some statistical machine-learning methods where continuous data must be processed or handled [4][5][6][7][8]. For example, when the value of the set of predictor variables is a continuous or real number, there will likely be very few observations that will have the same value.…”