Leveraging entrepreneurial ecosystems as human resource systems: A theory of meta-organizational human resource management

Cao

Wireless Communications and Mobile Computing

et al. 2022

The study is aimed at solving the security problems caused by malicious network attacks in human resource management in the development of smart cities. First, the Stackelberg game theory model is used to describe the interaction between intelligent sensors and intelligent jammers, and the security of the information physics system is effectively evaluated. Second, a denoise autoencoder machine model that can be used in human resource management with demographic information is proposed to ensure the security of intelligent sensors. Finally, its performance is simulated and analyzed. The results show that the more packets successfully arrive at the estimator, the more favorable the estimation effect of the estimator is. The designed defense strategy is very effective in protecting the security of intelligent sensors. When the number of nearest neighbor K increases, MAE of four datasets first decreases and then tends to be stable. With the increase of K , MAE of the algorithm proposed decreases from 0.8232 to 0.8095, 0.8086 to 0.7897, and 0.8563 to 0.8351, respectively. It decreases from 1.0169 to 1.0091 and then keeps stable. The recommendation algorithm proposed shows high accuracy in rating prediction and can quickly and effectively extract the hidden features of users and adjust the sparsity of data. Therefore, it can be applied to human resource management. This study provides a new idea for the research on the security of intelligent sensors and human resource management in the development of smart cities.

Section: Research Status Of Human Resource Managementmentioning

confidence: 99%

Security of Intelligent Sensors and Their Collaborative Roles in Human Resource Management in the Development of Smart Cities

Cao

Wireless Communications and Mobile Computing

et al. 2022

“…Through particular recruiting and selection, training and career development, performance assessment, and compensation procedures, HRM techniques attempt to improve the flow of knowledge—knowledge acquisition, absorption, transformation, and exchange activities in the business ( Roundy and Burke-Smalley, 2021 ). HRM techniques enhance an organization’s human capital foundation while focusing on less apparent value-generating elements such as engagement and knowledge embedded in scalar networks ( Ahmad et al, 2021 ).…”

Section: Theoretical Underpinning and Hypothesis Developmentmentioning

confidence: 99%

Internationalization Issues in Chinese Firms: One Belt, One Road-Based Perspective

2022

Front. Psychol.

The underlying aim of this study was to investigate the impact of human resource management (HRM) practices, organizational identity, and brand leadership on employee brand-based equity through the mediatory role of brand knowledge dissemination. A questionnaire was adopted to obtain data from 421 employees working in the construction sector of China. The SmartPLS software was used to analyze the data with the help of a structural equation modeling (SEM) technique. The results revealed that HRM practices and organizational identity had a positive and significant relationship with employee brand-based equity, while brand leadership had no direct impact on employee brand-based equity. The results also revealed that brand knowledge dissemination mediated the relationship between independent variables (HRM practices, organizational identity, and brand leadership) and dependent variable (employee brand-based equity). Theoretically, this paper made a valuable contribution by examining the impact of HRM practices, organizational identity, and brand leadership on employee brand-based equity. In terms of practical implications, this study would obviously help the organizations to improve their employee brand-based equity through HRM practices and organizational identity.

“…An alternative method for identifying new employees is for entrepreneurs to leverage their local entrepreneurial ecosystems as inter-organizational talent management systems, which connect entrepreneurs with talent (Roundy and Burke-Smalley, 2021). Specifically, entrepreneurs can consult their local network of ecosystem participants for new employee recommendations.…”

Section: Theory Developmentmentioning

confidence: 99%

“…Social coordination represents the degree to which ecosystem networks are dense and connect ecosystem participants through strong relationships (Fang et al , 2021). In socially coordinated entrepreneurial ecosystems, the communities’ networks represent a “meta-expert directory” (Roundy and Burke-Smalley, 2021) that entrepreneurs can use to quickly identify “who knows what?” about entrepreneurship in the ecosystem. In this function, social networks benefit entrepreneurs and other ecosystem participants by acting as conduits for the location and transfer of information and best practices about the entrepreneurship process (Pittz et al , 2021).…”

Section: Theory Developmentmentioning

confidence: 99%

Artificial intelligence and entrepreneurial ecosystems: understanding the implications of algorithmic decision-making for startup communities

Roundy

2022

JEET

Self Cite

Purpose Entrepreneurs are increasingly relying on artificial intelligence (AI) to assist in creating and scaling new ventures. Research on entrepreneurs’ use of AI algorithms (machine learning, natural language processing, artificial neural networks) has focused on the intra-organizational implications of AI. The purpose of this paper is to explore how entrepreneurs’ adoption of AI influences their inter- and meta-organizational relationships. Design/methodology/approach To address the limited understanding of the consequences of AI for communities of entrepreneurs, this paper develops a theory to explain how AI algorithms influence the micro (entrepreneur) and macro (system) dynamics of entrepreneurial ecosystems. Findings The theory’s main insight is that substituting AI for entrepreneurial ecosystem interactions influences not only entrepreneurs’ pursuit of opportunities but also the coordination of their local entrepreneurial ecosystems. Originality/value The theory contributes by drawing attention to the inter-organizational implications of AI, explaining how the decision to substitute AI for human interactions is a micro-foundation of ecosystems, and motivating a research agenda at the intersection of AI and entrepreneurial ecosystems.