How HR analytics catalyzes bank competitiveness: Investigating the mediating role of data-driven decision-making and the moderating effect of organizational agility

Performance management (PM) is a common practice used by organizations to assess and manage employees’ work. Much of PM research is closely related to management practices. Corporations in the public and nonprofit sector continuously develop PM programs to ensure the sustainability of their organizations.
The study aims to analyze the impact of strategic human resources planning on the organizational performance of Jordanian public shareholding companies for senior management and functional unit managers (human resources, marketing, finance, and accounting). The researchers surveyed all the public shareholding companies registered with the Jordan Securities Commission (JSC) in 2019, wherein they found that only 60 companies applied strategic planning and human resources planning (HRP) together. Two hundred and twenty questionnaires were distributed in 52 companies surveyed, and 203 were adopted for statistical analysis. Several statistical methods were used, most notably the multiple regression analysis. The researchers found out a statistically significant impact of the strategic human resources planning (integration of HRP and strategic planning; strategic participation) on organizational performance. The results showed that adopting the strategic HRP dimensions leads to an increase in an organization’s overall productivity, employee satisfaction and reputation, as well as reduced operating costs. HR managers must understand the effectiveness of strategically designed HR practices across functions.

Nowadays, Big Data and Artificial Intelligence (AI) play an important role in different functional areas of marketing. Starting from this assumption, the main objective of this theoretical paper is to better understand the relationship between Big Data, AI, and customer journey mapping. For this purpose, the authors revised the extant literature on the impact of Big Data and AI on marketing practices to illustrate how such data analytics tools can increase the marketing performance and reduce the complexity of the pattern of consumer activity. The results of this research offer some interesting ideas for marketing managers. The proposed Big Data and AI framework to explore and manage the customer journey illustrates how the combined use of Big Data and AI analytics tools can offer effective support to decision-making systems and reduce the risk of bad marketing decision. Specifically, the authors suggest ten main areas of application of Big Data and AI technologies concerning the customer journey mapping. Each one supports a specific task, such as (1) customer profiling; (2) promotion strategy; (3) client acquisition; (4) ad targeting; (5) demand forecasting; (6) pricing strategy; (7) purchase history; (8) predictive analytics; (9) monitor consumer sentiments; and (10) customer relationship management (CRM) activities.

The study aimed to identify the level of practicing the human resources staffing process and the level of the employees’ job involvement in the Irbid District Electricity Company in Jordan; it also aimed to examine the impact of human resources staffing process on the employees’ job involvement. The study adopted the descriptive, analytical method, since it determines the characteristics of the phenomenon, describes its nature accurately and then determines the quality of the relationship between its variables. The study population included all the individuals in the senior and middle administrative levels by 100 individuals. To achieve the objectives of the study, the researchers prepared a questionnaire to examine the study variables. One hundred questionnaires were distributed to each manager, deputy manager, and department head in the Irbid District Electricity Company out of which the researchers retrieved 97 questionnaires valid for analysis. In order to analyze the data collected, the study relies on the Statistical Package for Social Sciences (SPSS) where the descriptive statistics for all the fields of the study were estimated. The correlation matrix was also used to determine the relationship between variables. Furthermore, multiple regressions were used to determine the impact of the independent variable on the dependent variable. The findings showed that the level of practicing the human resources staffing process and the employees’ job involvement at Irbid District Electricity Company (IDECO) was moderate. The findings of the study showed that the process of human resources staffing was positively associated with the job involvement where the Pearson coefficient was r= .851 and at level of significance of 0.00. The research data have also indicated that the human resources staffing process had a positive impact on the employees’ job involvement. The study recommended that the procedures of staffing in all organizations should focus on achieving the fit between the employee and his job through focusing on choosing employees whose knowledge, skills and abilities correspond to the requirements of vacant jobs and also through implementing different tests and selection interviews, which help choose the person whose traits fit the job requirements. The study has also indicated that the recommended organizations should also pay attention to the job design process where the focus is on designing jobs in a way that creates a challenge, and enables employees feel independence and joy during the job; in this method, the employee can be more involved and can work in an effective way.