r. baradaran kazemzadeh

In this paper, the problem of finding profitable pairs by automatically limiting the search space of pairs using machine learning techniques and integrating an unsupervised learning algorithm, OPTICS, to pair identification and selection in pair trading is discussed. In addition, to optimize the portfolio consisting of pairs of assets and allocate optimal capital to them, a genetic-based algorithm to increase the Sharpe ratio is used. The proposed technique for automatic clustering is better than the conventional methods of searching for pairs of assets used by investors and leads to a higher average rate of return on investment and a higher Sharpe ratio for portfolios in trading using selected pairs of clusters. These calculated evaluation criteria for the portfolio were improved after using a bi-objective optimization genetic algorithm. This study was simulated using intraday price data of a group of stocks in the Tehran Stock Exchange between the years 2015 to 2020 and taking into account the transaction costs.

In this paper, a mathematical negotiation mechanism is designed to minimize the negotiators’ costs in a distributed procurement problem at two echelons of an automotive supply chain. The buyer’s costs are procurement cost and shortage penalty in a one-period contract. On the other hand, the suppliers intend to solve a multi-period, multi-product production planning to minimize their costs. Such a mechanism provides an alignment among suppliers’ production planning and order allocation, also supports the partnership with the valued suppliers by taking suppliers’ capacities into account. Such a circumstance has been modeled via bi-level programming, in which the buyer acts as a leader, and the suppliers individually appear as followers in the lower level. To solve this nonlinear bi-level programming model, a hybrid algorithm by combining the particle swarm optimization (PSO) algorithm with a heuristic algorithm based on A* search is proposed. The heuristic A* algorithm is embedded to solve the mixed-integer nonlinear programming (MINLP) sub-problems for each supplier according to the received variable values determined by PSO system particles (buyer’s request for quotations (RFQs)). The computational analyses have shown that the proposed hybrid algorithm called PSO-A* outperforms PSO-SA and PSO-Greedy algorithms.

Abstract

Organizational culture and employee attitude towards information technology are considered as the factors influencing successful implementation of information systems. The aim of this research was to determine the related factors to Hospital Information System (HIS) acceptance according to Competing Values Framework.

In this descriptive-correlative study، the conceptual model was proposed according to the related literature، and it was confirmed by the views of 7 experts. The two-part questionnaire including «HIS Acceptance» and «Organizational Culture Assessment Instrument» with total of 90 questions was developed based on the model variables. The validity of the questionnaire was obtained by content validity ratio، and its reliability was measured by calculating Cronbach’s Alpha. The research data was gathered through distributing the questionnaires among 400 users of HIS in the considered hospitals by using stratified sampling method. To test the conceptual model، Structural Equation Modeling and path analysis methods were used by applying LISREL Software version 8. 7.

The Normed Chi Square Index (1. 88) showed that the model had fitness with the gathered data. The indices included Goodness of Fit Index=0. 98، Comparative Fit index= 0. 98، Adjusted Goodness of Fit index=0. 94، Root Mean Square Error of Approximation= 0. 047. According to the research model، the correlation of developmental culture and Perceived Usefulness (P=0. 020) and the correlation of developmental، also hierarchical cultures and HIS use (P=0. 019) were statistically significant.

The results of testing the research model indicated that developmental and hierarchical cultures are related to HIS acceptance. In order to facilitate and improve HIS acceptance، it is recommended that the related authorities embark on fostering an environment with tendency towards developmental and hierarchical culture in the hospitals.

I ssues related to organizations and users are among factors influencing successful implementation of information systems. These factors should be taken into account by managers. The purpose of this study was to examine the influence of supervisors and workgroup on Hospital Information System (HIS) acceptance by users in medical hospitals of Tehran (former Iran) University of Medical Sciences.

After the literature review، a primary model including seven variables influencing HIS acceptance was proposed. A questionnaire including 121 questions based on the variables was developed، the validity and reliability of which were tested and confirmed by an expert panel and through Chronbach Alpha. The population of the study were 400 HIS users in hospitals selected by stratified random sampling method. To confirm the model and determine the relationship between variables، Structural Equation Modeling (SEM) method was used by applying LISREL Software.

The result of Normed Chi Square Index (χ 2 /df= 2. 49) showed that the model had fitness with the collected data. According to the model، supervisers and workgroup influenced Perceived Ease of Use، Perceived Usefulness، and Satisfaction which affected users Behavioral Intention to use Hospital Information System in these hospitals (P-value= 0. 0054).

Considering the goodnesss of fit indices، it is concluded that supervisors and workgroup factors have the potential to influence HIS acceptance. The application of the suggested model could increase the possibility of HIS acceptance in hospitals under the study.