*3.4. Data Analysis*

In addition, the Fuzzy Delphi method was chosen as the analysis technique to obtain the agreement of experts, namely the professionals, based on the study objectives. The Fuzzy Delphi method is a Delphi method performed to obtain information regarding consensus on measurement variables or factors from a group of experts [108,109]. The Delphi Method has been shown to be effective in publishing the best ideas/views through collective responses from expert informants [110]. With the principle of "more minds are better than a single mind", the Fuzzy Delphi method is designed as a forecasting tool to gather the ideas of structured groups, which are said to be more accurate than unstructured predictions [111]. This technique allows experts to coordinate their actions systematically in addressing a particular problem or difficulty and reach a consensus.

In this study, expert consensus was evaluated based on the seven MSCF domains, namely the smart economy, smart living, smart environment, smart people, smart government, smart mobility, and smart digital infrastructure. Each of these domains has its own strategic initiatives to enable cities in Malaysia to achieve smart city status. Respondents' understanding and acceptance were analyzed to achieve the objectives of the study.

Questionnaire data obtained from the focus group feedback of professionals were analyzed using a formulated Microsoft Excel worksheet by [106]. The experts' score inputs were evaluated in stages. Mathematical scores—the Likert scale and the triangular fuzzy scale scores for each item—were obtained (Table 9) and converted into mean values. Later, the threshold value (*d*), the percentage of expert agreement and the "defuzzification" process of the fuzzy score with *α*-cut value were calculated. Finally, based on the above three criteria, the ranking positions of the consensus items accepted/rejected by the expert panel were analyzed.


**Table 9.** Triangular fuzzy number scale [106].

In detail, let us say the item "I am ready to use e-payment in my daily affairs" was scored 5 (strongly agree) by an expert. The score is converted into the minimum, most plausible, and maximum values of 0.6, 0.8, and 1.0 fuzzy scores. It indicated the expert is agreeable to the item is 60%, 80%, and 100%, respectively. Then, the fuzzy scale of (0.6, 0.8, 1.0) is converted into mean value (*m*) among the 40 responds.

Next, according to [112], the calculation of the threshold (*d*) value performed was as follows:

$$d(\overline{m}, \overline{n}) = \sqrt{\frac{1}{3} [\left(m\_1 - n\_1\right)^2 + \left(m\_2 - n\_2\right)^2 + \left(m\_3 - n\_3\right)^2]}\tag{1}$$

where,

*d* = the threshold value,

*m*<sup>1</sup> = the smallest mean value of a fuzzy number,

*m*<sup>2</sup> = the most plausible mean value of a fuzzy number,

*m*<sup>3</sup> = the maximum mean value of a fuzzy number,

*n*<sup>1</sup> = the smallest value of a fuzzy number,

*n*<sup>2</sup> = the most plausible value of a fuzzy number, and

*n*<sup>3</sup> = the maximum value of a fuzzy number.

The value of '*d*' (the threshold value) for all items of the questionnaire indicates expert consensus agreement for each item. According to [112], the value of '*d*' must be greater than or equal to 0.2 to indicate consensus agreement for each item.

For the expert agreement/consensus percentage, if the expert consensus exceeded 75%, it was considered accepted [113,114]. Then, through the process of defuzzification or the process of determining the scores, the ranking positions of each item were determined. The formula used to determine the ranking/score for an item was as follows:

$$A\_{\max} = \frac{1}{3}(m\_1 + m\_2 + m\_3) \tag{2}$$

After an assessment was made, if the fuzzy (*Amax*) score or *α*-cut value was equal to or exceeded 0.5, this indicated expert consensus to accept the item [115].

The Delphi method is a widely accepted, efficient, and effective way of bringing together experts to discuss, debate, and organize a body of information in order to develop a validated instrument, reach agreement on an issue, uncover common factors, or forecast trends [116,117]. This method is deemed particularly highly reliable when more than ten experts in the given field were employed [105,106]. Additionally, to minimize the bias, it is important to involve experts in a study that possess extensive experience, high qualifications, and knowledge in the field or the subject matter [118]. Evidently, this study meets these requirements as it has involved 40 experts with a minimum of five-year work experience, possessed at least a bachelor's degree, and involved intensively in the planning and management of smart cities in the context of Malaysia (Table 8). Hence, we did not employ an additional validation mechanism for the generated results of the Delphi study.
