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Considerable research has been conducted to highlight women's career decisions to opt-out of corporate positions, but little is said about those who leave to become entrepreneurs. The purpose of this paper is to theorize kaleidoscope career parameters in relation to entrepreneurship stages and demonstrate the role of macro-national context (i.e. government initiatives and cultural practices) in women entrepreneurs' career choices.

The authors interviewed 34 Malaysian women entrepreneurs (MWEs) who were established in their careers and explored the following two research questions: (1) what career parameters are prioritized at different entrepreneurship stages? and (2) how does macro-national context influence women entrepreneurs' careers?

Adopting a kaleidoscope career lens, the authors show that authenticity was prioritized during the initial entrepreneurship stage, while balance and challenge were prioritized during the establishment and business advancement stages, respectively. The authors demonstrate that government support was conducive to women's decision to opt-in and stay in the entrepreneurship path. The findings also denote that cultural practices facilitated women's pursuit of entrepreneurship by encouraging family members to support women entrepreneurs in their career choices and actions.

The qualitative approach enabled us to specify the context-specific meaning women entrepreneurs in our study associated with authenticity, balance, and challenge. In doing so, this research extends the kaleidoscope career model to better understand women's career patterns at different entrepreneurship stages.

The purpose of this paper is to examine the possibility of developing emotional intelligence (EI) as conceptualized in Boyatzis et al.'s competency model.

Designing a context‐based EI training program, the study utilized a sample of 68 fully‐employed members of five branches of a public bank in Iran; each branch underwent an eight‐week (each session 120 minutes) EI training program. Pre‐ and post‐tests were conducted to assess EI development using emotional competence inventory (ECI‐2), a 360‐degree measurement tool.

Only one EI cluster out of four improved significantly and only some of the specific dimensions showed this significant improvement, while others did not have a clear change and even some self assessments deteriorated.

Lack of a control group, small sample size, and short training program are the main limitations of this study.

Detailed explanation of the method could be a guide for service organizations that wish to improve EI.

Because of the lack of empirical studies in this field of research, the paper reports the results of a pre‐/post study on EI training and development and sets out to add to this narrow literature.

The purpose of this study is to investigate the effects of an emotional intelligence (EI) training program on: the EI of service providers; and the service quality provided by employees who have received such training.

Employees of five branches of a large public‐sector bank in Iran are randomly selected as the “treatment group” to undertake a tailored eight‐session EI training program, while employees of another homogenous sample of five branches are selected as the “control group” (involving no EI training). EI is measured by the ECI‐2 instrument before and after training. Two samples of customers (150 customers of the “treatment branches” and 150 customers of the “control branches”) are utilised to evaluate the perceived service quality of both groups of branches before the training and two months after the training.

One of four dimensions of EI (“relationship management”) is found to be enhanced by EI training. Moreover, the EI training program is shown to result in improved service quality in terms of both overall service quality and its four dimensions (“reliability”, “responsiveness”, “assurance”, and “empathy”).

Operational constraints prevented a second assessment of the EI of employees in the control group. The post‐training evaluations had to be conducted shortly after the training finished, thus preventing an assessment of longer‐term effects.

This is one of the first studies to have undertaken empirical investigation of the effectiveness of EI training in a service setting.

The purpose of this paper is to investigate the relationship between work‐family conflict and its antecedent variables. The research's dependent variables include work interference with family (WIF) and family interference with work (FIW). Independent variables consist of work‐related (hours spent at work, role conflict, role ambiguity, supervisor support, and work shifts), family‐related (hours spent with family, marital status, spousal employment, number of children, and age of the youngest child), and demographic (gender, age, tenure, and education) variables.

In total, 333 operating room personnel in ten Iranian hospitals completed a survey questionnaire, which consisted of 38 questions administered to participants in the workplace.

Analysis of data revealed that among work‐related variables, the role conflict was positively associated with WIF. Supervisor support and working shifts were also weakly related to WIF. No significant relationships were found between family‐related variables and FIW. Among the demographic variables, only gender influenced FIW in a manner that men experienced more FIW than women.

The research findings contribute to understanding work‐family conflict in a new cultural setting. The empirical evidence of work‐family conflict in Iran, among operating room personnel, shows that experiences and antecedents of work‐family conflict vary among diverse cultures and industries. Models of work‐family conflict may need to be modified to reflect the experiences and antecedents that explain work‐family conflict in cultures similar to that of Iran.

The purpose of this research is to determine whether Iranian student attitudes toward teamwork are relatively favorable or unfavorable. The authors also examine the influence of variables that affect student attitudes toward teamwork, including concerns about teamwork evaluation and perceptions of the environment for teamwork, gender, age, GPA, education level, major, and teamwork training.

A questionnaire developed to measure the study variables was administered to 1,811 students across different majors in three large Iranian universities.

The results indicate that Iranian students have moderately positive attitudes toward teamwork, contrary to the prevalent belief that Iranians are not much interested in teamwork. The results indicate that Iranian students are concerned about how teamwork is evaluated. They believe that the environmental facilities at their universities for teamwork are weak and not supportive. Structural equation modeling showed that student concerns about teamwork evaluation and their perceptions of environmental facilities influence their attitudes toward teamwork. Positive teamwork attitudes are moderately reinforced when students are less concerned about evaluation and when the physical facilities support teamwork activities. Further analysis showed that male students have a slightly better attitude toward teamwork than women.

The findings are valuable to practitioners who may employ current students in the future, and to instructors who plan to include teamwork in their course assignments.

This study was designed to fill the void in the knowledge about Iranian student attitudes toward teamwork and variables that influence this attitude.

The behavioural changes embraced by the current generation has prompted researchers to revisit the paradigm of human relationships, especially romantic liaisons. The present study revisits the construct of romantic relationships steered by social media platforms, through the dimensions of self-disclosure, social intimacy and trust. The role of trust as a mediator to determine the success of online dating is also explored in this study.

The study uses the data collected from 225 respondents (86 females and 139 males) in the age group of 18 to 30 years. The respondents were asked to fill a questionnaire (provided they fulfilled the necessary conditions and expressed their consent to be a participant in this study).

The study validates that the extent of self-disclosure propels the degree of social intimacy. The results also confirm a significant partial mediation effect of trust on the relationship between social intimacy and the success of online dating. Thus, practitioners need to keep in mind that the probability of online dating success is higher when individuals disclose more and engage in an intimate relationship driven by trust.

The study sample is restricted to young adults ranging from 18 to 30 years, based on the author’s convenience. The study was restricted to three most popular social media platforms in India where disclosure is limited to private timelines or messages. Another limitation of this study is that a multi-variate model of analysis could not be used due to the lack of parallel variables. Further studies can also compare online versus offline dating behaviour and determinants that influence the romantic relationship between two partners.

The new perspective could be to ascertain specific built-in mechanisms providers should develop to ensure that the new generation benefits from new technology rather than falling victim to its toxins.

The study re-establishes the importance of the role of trust in any romantic relationship – may it be online or the more traditional, offline or face-to-face mode.

The study delves into the domain of existing romantic relationships established through the modernistic viewpoint of online social media platforms. The findings bring a fresh perspective on the dynamics of online romantic relationships through the mélange of self-disclosure, social intimacy and trust. Previous literature suggests that trust is dependent on self-disclosure, which is in contrast with the results of the current study. The present study corroborates that trust leads to the success of online dating.

It is well known in the mining industry that the increase in failures and breakdowns is due mainly to a poor maintenance policy for the equipment, in addition to the difficult access that specialized personnel have to combat the breakdown, which translates into more machine downtime. For this reason, this study aims to propose a remote assistance model for diagnosing and repairing critical breakdowns in mining industry trucks using augmented reality techniques and data analytics with a quality approach that considerably reduces response times, thus optimizing human resources.

In this work, the six-phase CRIPS-DM methodology is used. Initially, the problem of fault diagnosis in trucks used in the extraction of material in the mining industry is addressed. The authors then propose a model under study that seeks a real-time connection between a service technician attending the truck at the mine site and a specialist located at a remote location, considering the data transmission requirements and the machine's characterization.

It is considered that the theoretical results obtained in the development of this study are satisfactory from the business point of view since, in the first instance, it fulfills specific objectives related to the telecare process. On the other hand, from the data mining point of view, the results manage to comply with the theoretical aspects of the establishment of failure prediction models through the application of the CRISP-DM methodology. All of the above opens the possibility of developing prediction models through machine learning and establishing the best model for the objective of failure prediction.

The original contribution of this work is the proposal of the design of a remote assistance model for diagnosing and repairing critical failures in the mining industry, considering augmented reality and data analytics. Furthermore, the integration of remote assistance, the characterization of the CAEX, their maintenance information and the failure prediction models allow the establishment of a quality-based model since the database with which the learning machine will work is constantly updated.