Achieving Strategic Alignment of Big Data Projects in Saudi Firms

Big data projects can fail due to the lack of alignment between the big data project strategy and the overall business strategy. This research considers organizational culture as an enabler of a better alignment between the two. To test the research hypothesis, a questionnaire was collected from several dozen IT decision-makers in Saudi organizations who have implemented big data projects. Statistical analysis using PLS indicates that the alignment of big data projects and overall business strategy is highly influenced by the five dimensions of organizational culture identified by Smit et al. (2008), namely strategy, leadership, adaptability, coordination, and team relationships

The framework of talent analytics using big data

Purpose

The era of work 4.0 demands organizations to expedite their digital transformation to sustain their competitive advantage in the market. This paper aims to help the human resource (HR) department digitize and automate their analytical processes based on a big-data-analytics framework.

Design/methodology/approach

The methodology applied in this paper is based on a case study and experimental analysis. The research was conducted in a specific industry and focused on solving talent analysis problems.

Findings

This research conducts digital talent analysis using data mining tools with big data. The talent analysis based on the proposed framework for developing and transforming the HR department is readily implementable. The results obtained from this talent analysis using the big-data-analytics framework offer many opportunities in growing and advancing a company's talents that are not yet realized.

Practical implications

Big data allows HR to perform analysis and predictions, making more intelligent and accurate decisions. The application of big data analytics in an HR department has a significant impact on talent management.

Originality/value

This research contributes to the literature by proposing a formal big-data-analytics framework for HR and demonstrating its applicability with real-world case analysis. The findings help organizations develop a talent analytics function to solve future leaders' business challenges.

Give Me What I Want: Identifying the Support Needs of College Student Entrepreneurs

To determine how the success rate of college students’ entrepreneurship can be improved, we sought to identify the support needs of undergraduate entrepreneurs and evaluate the importance of different support needs using data from face-to-face interviews with 138 Chinese college student entrepreneurs. Further, we explored the distribution tendencies of the support needs at different entrepreneurial stages. We found that the support needs of college student entrepreneurs can be divided into 20 types, which can be categorized into core support needs (six types), secondary support needs (six types), and marginal support needs (eight types) in descending order of importance. A cross-stage analysis indicates that the support needs differ during the different entrepreneurial stages. While the needs during the entrepreneurial preparation stage and the startup stage have many similarities, those during the entrepreneurial failure stage are significantly different from those of the other three stages examined, showing heterogeneity. In addition, we identified psychological counseling as an important core support need in the failure stage and demonstrate its critical role in helping college students out of the shadow of entrepreneurial failure. This study expands the research on entrepreneurial support needs. Its findings provide valuable information to help colleges and governments develop more targeted and appropriate support for college entrepreneurs based on entrepreneurial stages to promote entrepreneurial success.