درخت حوزه‌های تخصصی

Antecedents destructive organizational behaviors impose many direct and indirect costs on organizations, therefore, in the current situation, paying attention to it has gone beyond a choice and has become a necessity. This research was done with the aim of identifying the antecedents of destructive organizational behavior in the banking system. The type of research is developmental in terms of purpose. For this purpose, after searching the databases, 582 articles were evaluated in the field of destructive organizational behaviors between 2000 and 2022, and finally, 55 articles were selected in a targeted way and entered the analysis stage. Based on the final framework of the research, the antecedents of destructive organizational behaviors were categorized in the form of two main categories and six subcategories. The main categories resulting from the research results are: facilitating antecedents and limiting antecedents of destructive organizational behaviors. Facilitating and limiting antecedents of destructive organizational behaviors each includes three categories of behavioral, structural, and contextual facilitating and limiting factors. The obtained framework can be used as a tool for strategic planning in the field of destructive organizational behaviors.

Purpose: The purpose of this research was primarily to design the electronic customer relationship management model and explain its consequences.Method: Validation of electronic customer relationship in private banks based on mixed research and descriptive-exploratory method were used. On this basis, with the help of data-based theorizing method, the categories forming the model were identified by open coding, and then with the benefit of central and selective coding, the desired model was presented. Also, in the following, the validation of the model among the studied population was discussed using the method of structural equation modeling. The statistical population for presenting the model includes banking industry experts (consisting of senior bank managers with at least 10 years of work experience and academic experts in the field of digital marketing with at least 5 years of experience working in the banking system) and for validating the model two categories of managers and employees of private banks. The research is limited to the city of Tehran and the local customers . The statistical sample of experts up to the stage of theoretical saturation is 16 people using a purposeful judgemental method, and for the model validation stage, 230 people were selected based on the rules of sample size in the structural equation method. The data collection tool included a semi-structured interview for the modeling stage and a questionnaire with a five-point Likert scale for the validation stage.Findings: The findings showed that 67 basic themes (selective concepts) were categorized and after reviewing, 20 organizing themes (dimensions) were obtained and finally these dimensions were divided into 7 general categories: organizational factors, individual factors, contextual factors, environmental factors, frameworks, strategies, consequences were categorized. The main category identified in this research is "Implementation of E-CRM" and other categories are presented under the headings of causal conditions, background factors, strategies, and consequences.Conclusion: The results of the calculated value (GOF) for the structural model of the research was calculated as 0.387, which indicates the overall strong performance of the structural equation model of the research. Also, the findings of the quantitative part have confirmed the validity of the structural model of the research and demonstrated the truth of hypotheses of the research (except for hypotheses No. 9, 11, 15, 16, and 17)

Bali tourism faced conflict with the local community because of the utilization and commodification of sacred and forest areas. The first sacred area conflict occurred in 1994, based on the use of the sacred land “Tanah Lot” become tourists resort namely Bali Nirvana Resort (BNR). Furthermore, this problem is presently observed in the utilization of mangrove forests for the international airport and LNG (liquefied natural gas) terminals, respectively. In these conflicts, all facilities are designed to support the increase in the inbound tourist visits and foreign investment. This growth of Bali tourism threatens the development of sustainable tourism, which concerned with environment, local communities and local economy, but spiritual tourism creates the conflict subsided due to the dependence of spiritual tourism on sacred areas, the environment, and local community resources. Therefore, this study aimed to evaluate Corporate Social Responsibility (CSR) of spiritual tourism in building sustainable economy based on the local wisdom of Bali Tri Hita Karana. Data were qualitatively analyzed and obtained from literature reviews, observations, and in-depth interviews. The results showed that spiritual tourism emphasized sacred areas, the surrounding natural environment, and local community assets. This dependence developed a mutually beneficial relationship, subsequently leading to the CSR of Spiritual Tourism. The CSR based on the local wisdom Tri Hita Karana which create harmonious between the local people, environment, and investment.

Internet-based social channels have turned into an important information repository for many people to get an idea about current trends and events happening around the world. As a result of Abundance of raw information on these social media platforms, it has become a crucial platform for businesses and individuals to make decisions based on social media analytics. The ever-expanding volume of online data available on the global network necessitates the use of specialized techniques and methods to effectively analyse and utilize this vast amount of information. This study's objective is to comprehend the textual information at the Lexical and Semantic level and to extract sentiments from this information in the most accurate way possible. To achieve this, the paper proposes to cluster semantically related words by evaluating their lexical similarity with respect to feature and sequence vectors. The proposed method utilizes Natural Language Processing, semantic and lexical clustering and hybrid C4.5 algorithm to extract six subcategories of emotions over three classes of sentiments based on word-based analysis of text. The proposed approach has yielded superior results with seven existing approaches in terms of parametric values, with an accuracy of 0.96, precision of 0.92, sensitivity of 0.94, and an f1-score of 0.92.