Search results

The purpose of this paper is to develop an instrument to measure employer branding in the information age. Firms increasingly migrate from matter-intensive business models to information-intensive models, where value lies in information rather than the physical objects. This shift has, in turn, led to a change in employee work skills. This is particularly true in the information technology (IT) sector, where firms rely on a limited supply of skilled labor. Employer branding, a firm’s reputation as a place to work, is an important strategy to attract and retain employees.

From the literature, the authors developed and refined an instrument to measure key value propositions of employer brands. The potential IT employees surveyed in the study were students enrolled in the disciplines of computer science and information systems at a comprehensive university in North America. The study went through three stages resulting in an instrument for psychometric properties.

This research revealed eight employer branding value propositions that future IT employees care about. These dimensions are important for both IT firms and industries competing for skilled IT labor to understand and manage.

This paper extends the work of Berthon et al. (2005) on employer branding to the information intensive age and particularly the IT sector. It allows executives to manage and measure their employer brand so as to maximize competitive advantage in attracting and retaining skilled employees.

Online brand communities provide a wealth of insights about how consumers perceive and talk about a brand, rather than what the firm communicates about the brand. The purpose of this paper is to understand whether the brand personality of an online brand community, rather than of the brand itself, can be deduced from the online communication within that brand community.

The paper is empirical in nature. The authors use community-generated content from eight online brand communities and perform content analysis using the text analysis software Diction. The authors employ the five brand personality dictionaries (competence, excitement, ruggedness, sincerity and sophistication) from the Pitt et al. (2007) dictionary source as the basis for the authors’ analysis.

The paper offers two main contributions. First, it identifies two types of communities: those focusing on solving functional problems that consumers might encounter with a firm’s offering and those focusing on broader engagement with the brand. Second, the study serves as a blueprint that marketers can adopt to analyze online brand communities using a computerized approach. Such a blueprint is beneficial not only to analyze a firm’s own online brand community but also that of competitors, thus providing insights into how their brand stacks up against competitor brands.

This is the first paper examining the nature of online brand communities by means of computerized content analysis. The authors outline a number of areas that marketing scholars could explore further based on the authors analysis. The paper also highlights implications for marketers when establishing, managing, monitoring and analyzing online brand communities.

The purpose of this paper is to introduce, apply and compare how artificial intelligence (AI), and specifically the IBM Watson system, can be used for content analysis in marketing research relative to manual and computer-aided (non-AI) approaches to content analysis.

To illustrate the use of AI-enabled content analysis, this paper examines the text of leadership speeches, content related to organizational brand. The process and results of using AI are compared to manual and computer-aided approaches by using three performance factors for content analysis: reliability, validity and efficiency.

Relative to manual and computer-aided approaches, AI-enabled content analysis provides clear advantages with high reliability, high validity and moderate efficiency.

This paper offers three contributions. First, it highlights the continued importance of the content analysis research method, particularly with the explosive growth of natural language-based user-generated content. Second, it provides a road map of how to use AI-enabled content analysis. Third, it applies and compares AI-enabled content analysis to manual and computer-aided, using leadership speeches.

For each of the three approaches, nine steps are outlined and described to allow for replicability of this study. The advantages and disadvantages of using AI for content analysis are discussed. Together these are intended to motivate and guide researchers to apply and develop AI-enabled content analysis for research in marketing and other disciplines.

To the best of the authors’ knowledge, this paper is among the first to introduce, apply and compare how AI can be used for content analysis.

The efficiency of each of an organization’s individual workers determines its effectiveness. The study aims to explore the relationship between human resource management (HRM) practices and organizational effectiveness with employee performance as a mediating variable.

Data were collected from 800 police officers in the Greater Accra and Tema regions. The data were supported by the hypothesized relationship. Construct reliability and validity was established through confirmatory factor analysis. The proposed model and hypotheses were evaluated using structural equation modeling.

The results show that career planning and employee performance were significantly related. Self-managed teams and employee performance were shown to be nonsignificantly related. Similarly, performance management and employee performance were shown to be nonsignificantly related. Employee performance significantly influenced organizational effectiveness. The results further indicate that employee performance mediates the relationship between HRM practices and organizational effectiveness.

The generalizability of the findings will be constrained due to the research’s police service focus and cross-sectional data.

The study’s findings will serve as valuable pointers for the police administration in the adoption, design and implementation of well-articulated and proactive HRM practices to improve the abilities, skills, knowledge and motivation of officer’s to inordinately enhance the effectiveness of the service.

By evidencing empirically that employee performance mediates the relationship between HRM practice and organizational effectiveness, the study extends the literature.

In economic crisis, where tensions create anxiety and test the emotions of the firms' shareholders, communication from top management is very crucial as it provides the reflection of the managers' interpretation of the firms' situation and potential strategies. The goal of this paper is to investigate the relationships between sentiment, as an aspect of emotions extracted from the letters to shareholders, managerial discretion and the firms' subsequent performance and performance trajectory during crisis.

A sentiment analysis was conducted to extract the sentiment from the letters to shareholders, which were collected from firms in two countries with different levels of managerial discretion (US vs. Japan). Hypotheses were developed and tested using a series of regression analysis.

The primary findings indicate that (1) managerial sentiment identified in letters to shareholders can potentially be related to the firm's subsequent performance in the economic crisis, and (2) managerial discretion moderates the relationship between managerial sentiment and subsequent firm performance.

When the managerial discretion is high, firms' shareholders can use the sentiment in top management communications to gauge whether the firms' situation would be improving in the near future.

This study expands the current research on sentiment analysis and firm performance to the context of economic crisis by suggesting that managerial sentiment can be substantially provoked as firms are facing with stressful economic conditions. The study also highlights the moderating role of managerial discretion on the firms' subsequent performance.

This paper aims to identify the unidimensionality and reliability of 84 factors that influence the performance of construction projects and develop a confirmatory factor analysis (CFA) model.

The study adopted a deductive research approach and started by identifying the positive factors that influence construction project performance. This was followed by the modification of the identified factors. After that, a questionnaire was developed out of the factors for data collection. Exploratory factor analysis was used to establish the factor structure of the positive factors, and this was verified using CFA afterwards. A model fit analysis was performed to determine the goodness of fit of the hypothesised model, followed by the development of the confirmatory model.

The study demonstrated substantial correlation in the data, sufficient unidimensionality and internal reliability. In addition, the estimated fit indices suggested that the postulated model adequately described the sample data.

The paper revealed that performance can be enhanced if stakeholders identify and leverage the positive factors influencing performance. The paper suggests that project stakeholders, particularly government, project owners, consultants and construction firms, can improve project performance by critically examining economic and financial systems (EFS), regulation and policy-making systems (RPS), effective management practices (EMP) and project implementation strategies (PIS).

The contribution of this paper to the present literature is identifying the positive factors and developing the confirmatory factor model. The model comprised 42 positive variables under four indicators: EMP, RPS, PIS and EFS.