Nowadays, there are many municipalities have provided mobile services related to their smart city implementations. Therefore, citizens can use mobile services at anytime and anywhere [1]. The object of our research is to understand what criteria afect consumers' tendency to use smart city mobile services. We focused on three measurement dimensions for quality: system quality, information quality, and service quality and five dimensions for usability: efectiveness, eficiency, satisfaction, learnability, and security to assess consumers' attitudes. In addition, for usability assessment focalize as a combination of efectiveness, eficiency, satisfaction, learnability, and security. This paper combined the DEMATEL approach to cope with the problem of interdependence exists among criteria, and to select an optimal portfolio of smart city mobile consumers' attitude.
ter of information examination and have broadened the capability of utilizing information driven instruTo make a good decision, the ability to forecast the ments through dynamic procedures. Business analytoutcome of the available options is very important. ics, as an emerging research area, strives to bring difThe original decision support systems (DSS) concept ferent fields and disciplines together overlaying diverse was clearly defined by Gorry and Scott Morton, as “is aspects in terms of technological innovations, quantithe system that supports any managerial activity in tative/numerical methods, and decision-making. semi structured or unstructured decisions”. They also Data analytics refers to the information technolodefined that characteristics of information requiremen- gies that are grounded mostly in three main types whits and decision models difer in a decision support sys- ch are descriptive, predictive and prescriptive. Descriptems environment. The reason of the diference is that tive analytics examine data in detail to reveal the freDSS is defined in terms of the addressed task struc- quency of cases, the cost of processes, and the base ture. Most study on DSS focuses on the adaptive pro- cause of collapse. It ensures meaningful insight into cesses about design strategy, decision research and im- activity performance and facilitate users to better folplementation strategy. low up and operate their work processes. Predictive
Strategy implementation is the conversion of select- analytics use models and techniques to estimate
forthed tactics into organizationasl activity so as to acquire coming results based on historical and streamed data.
strategic targets and objectives [
In this respect, a novel business analytics approach ential. Furthermore, the concept of prescriptive
anis proposed in this paper for smart city administra- alytics in decision support systems in the smart city
tion and getting a grip on three quality dimensions; context is introduced. In the smart city mobile
apsystem, information and service quality and five di- plications, system quality is a very significant factor
mensions for usability; efectiveness, eficiency, satis- to assess the extent of the all system resources [
DEMATEL methodology have been applied in many
contexts such as mobile banking [
Mobile application frameworks have found their way ified context of use”.
into regular day to day existence, and with an
extensive client base [
The proposed method has the four-step procedure. 1 Fdiirtisot,ntahleadttercibisuiotensgwoaelrsefeosrtasebglimsheendtintog dtheteeermighintecothne- = 1⩽ ⩽Σ =1 , , = 1, 2, … , significance of the factors afecting fragmentary end- Step 3: Attaining the total-relation matrix. Once the user usage. DEMATEL technique can convert the in- normalized direct-relation matrix X is obtained, the toterrelations between criteria into an intelligible struc- tal relation matrix T can be acquired by using Eq. 2 , tural model of the system and divide them into a cause where I is denoted as the identity matrix, group and an efect group [15]. DEMATEL is a practicable and beneficial tool to analyze the interdependent (2) relationships among elements in a complex framework and grade them for decision making. Thus, this technique can be used in prescriptive analysis. The formulating steps of the classical DEMATEL [16] can be = ⋅ ( − ) − 1
Step 4: Producing a causal diagram. The sum of rows and columns are separately denoted as vector D and vector R through equations in Eq. 3. The horizontal axis vector (D + R) named as “prominence” is made by adding D to R, which reveals the relative im- tained. Next, the total-relation matrix (Tab. 4) was acportance of each criterion. Similarly, the vertical axis quired. Following the step of DEMATEL method is (D - R) called as “relevance” is made by subtracting D created the total influence matrix. There shows the from R, which may divide criteria into a cause and efsum of the direct and indirect efects that factor has fect groups. Generally, when (D - R) is positive, the received from the other factors. The total influence criterion belongs to the cause group, (D - R) is negamatrix is defined the sum of the rows and the sum of tive, the criterion represents the efect group. Therethe columns separately which can be denoted as vector fore, the causal diagram can be obtained by mapping r and s the dataset of the (D + R, D - R), providing some insight for making decisions.
= [ , ] ×
, = 1, 2, … , = [Σ =1 , ] ×1 = [ ] ×1 = [Σ =1 , ]1× = [ ]1× where vectorD and vector R denote the sum of rows and columns in total-relation matrix T.
Step 5: Obtaining the inner dependence matrix. In this step, the sum of each column in total-relation matrix is equal to 1 by the normalization method, and then the inner dependence matrix can be acquired. At ifrst step of DEMATEL, attributes impact values have already asked to 5 diferent experts on working this ifeld. The impact value which is from 0 to 4 (0 means that there are not any afect and 4 means that there are relations with those attributes a very dramatically efective) has collected each diferent software developer. 5 experts are asked to identify the degree of influence between the factors or elements (criteria) to calculate the average matrix of influence matrix. In step 2, the experts adopted the eight attributes as evaluation factors. In step 3, once the relationships between those attributes were measured by the experts through the use of the scale, the data from each individual assessment could be obtained. Then, using the CFCS method to aggregate these assessment data, the initial directrelation matrix (Tab. 2 ) was produced. the normalized direct-relation matrix (Tab. 3) was ob
Let i=j and i,j ∈ { 1,2,...n }; the horizontal axis vector (r + s ) is then made by adding r to s , which illustrates the importance of the criterion. Similarly, the vertical axis vector (r - s ) is made by deducting
r from s , which may separate criteria into a cause (3) group and an afected group. In general, when (r is positive, the criterion is part of the cause group. On - s )
the contrary, if (r - s ) is negative, the criterion is part of the afected group. Therefore, a causal graph can be achieved by mapping the dataset of ( r + s ,r - s ), providing a valuable approach for decision-making. The
sum of influences is given and received on criteria will be shown in Tab 5. The direction of influence between dimensions and criteria can be visualized in Fig. 2. After all those analytics, the Integrated Natural Resource
attributes can be understood from Fig. 2. Moreover,
In step 4, based on the initial direct-relation matrix, a smart city application. In mobile application, mar
A2 -0,119 1,000 -0,090 -0,165 -0,060 -0,120 -0,124 -0,085 ket mobile devices and technology has continued to expand. Internet technology continues to grow that widely used mergers and action for mobile devices, has a channel operation trade in services, particularly in the rapidly. DEMATEL approach to cope with the problem of interdependence exists among the criteria, and to select an optimal portfolio of consumers’ inclination. This study the DEMATEL approach to consider the interdependencies among criteria and to obtain a priority of inclinations. Then, the DEMATEL provide a decision model for determining the final ranking of alternatives using the weights of each criterion of SCMA. So, the result of the priority for end user’ inclination first is “Information and Service Quality”, after that is “efectiveness”. Hope these results can help governors and city managers to evaluate how well each sourcing decision is able to approximate the expected maximum benefit.