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Online food delivery service has evolved swiftly and stretched the bounds of the catering business. In the gig economy, being a food delivery rider draws employees with the promise of flexibility and independence. To this end, the purpose of this paper is to explore the main themes shared in online reviews by food delivery riders and which of these themes are linked to positive and negative ratings.

The authors used 729 employee reviews posted on the Glassdoor website. In addition, they used content analysis to examine reviews of Uber Eats online food ordering company shared by food delivery riders on an online platform.

The results of this study include seven main themes: “earning,” “customers,” “orders,” “tips,” “car,” “flexible schedule” and “app” (navigation). Positive concepts are associated with “earning,” “orders,” “tips” and “flexible schedule.” Negative themes are linked to the “app” (navigation), “car” and “customers.”

Management should consider online reviews as employees’ opinions and voices. Specifically, management should provide financial support to employees for car maintenance, offer insurance for income stability and arrange training programs to enable them to use several tip-enhancing behaviors.

No research has been conducted using online reviews from an employment search engine to investigate employees’ experiences of online food delivery. To the best of the authors’ knowledge, this study is one of the first attempts using user-generated content from an employment search engine to explore employees’ experiences.

This study aims to help uncover corporate culture and values to attract and retain talent by understanding job reviews written by business-to-business (B2B) salespeople.

Over 40,000 job reviews on Glassdoor.com are analyzed by a dictionary-based content analysis tool, Linguistic Inquiry and Word Count (LIWC2015), to explore the links between corporate culture and linguistics characteristics of reviews as articulated by B2B salespeople. This study adopted a multidimensional scaling approach based on the nine cultural value scores to create a map of corporate profiles. A projection of the LIWC2015 scores on this map uncovers differences in language patterns and emotions expressed across the profiles.

Findings reveal a map of corporate profiles with two dimensions, namely, product-centricity and customer-centricity, that divide salesforce subculture into a 2 × 2 matrix of four types: Empathic Innovators, Product Pioneers, Customer Champions and Commodity Traders.

This study combined two data sets, scores on CultureX’s nine cultural values (agility, collaboration, customer orientation, diversity, execution, innovation, integrity, performance and respect) and job reviews on Glassdoor.com. This research seeks to develop profiles of the organizational culture and to use a blend of qualitative and quantitative methods. This study adds to the literature on salesforce subculture and showcases a solution to the methodological difficulty in categorizing and measuring culture.

Environmental, social and governance (ESG) factors have become increasingly important in investment decisions, leading to a surge in ESG investing and the rise of sustainable investment assets. Nevertheless, challenges in ESG disclosure, such as quantifying unstructured data, lack of guidelines and comparability, rampantly exist. ESG rating agencies play a crucial role in assessing corporate ESG performance, but concerns over their credibility and reliability persist. To address these issues, researchers are increasingly utilizing machine learning (ML) tools to enhance ESG reporting and evaluation. By leveraging ML, accounting practitioners and researchers gain deeper insights into the relationship between ESG practices and financial performance, offering a more data-driven understanding of ESG impacts on business communities.

The authors review the current research on ESG disclosure and ESG performance disagreement, followed by the review of current ESG research with ML tools in three areas: connecting ML with ESG disclosures, integrating ML with ESG rating disagreement and employing ML with ESG in other settings. By comparing different research's ML applications in ESG research, the authors conclude the positive and negative sides of those research studies.

The practice of ESG reporting and assurance is on the rise, but still in its technical infancy. ML methods offer advantages over traditional approaches in accounting, efficiently handling large, unstructured data and capturing complex patterns, contributing to their superiority. ML methods excel in prediction accuracy, making them ideal for tasks like fraud detection and financial forecasting. Their adaptability and feature interaction capabilities make them well-suited for addressing diverse and evolving accounting problems, surpassing traditional methods in accuracy and insight.

The authors broadly review the accounting research with the ML method in ESG-related issues. By emphasizing the advantages of ML compared to traditional methods, the authors offer suggestions for future research in ML applications in ESG-related fields.

Online employee reviews have emerged as a crucial information source for business managers to evaluate employee behavior and firm performance. The purpose of this paper is to test the relationship between employee personality traits, derived from online employee reviews and job satisfaction and turnover behavior at the individual level.

The authors apply text-mining techniques to extract personality traits from online employee reviews on Indeed.com based on the Big Five theory. They also apply a machine learning classification algorithm to demonstrate that incorporating personality traits can significantly enhance employee turnover prediction accuracy.

Personality traits such as agreeableness, conscientiousness and openness are positively associated with job satisfaction, while extraversion and neuroticism are negatively related to job satisfaction. Moreover, the impact of personality traits on overall job satisfaction is stronger for former employees than for current employees. Personality traits are significantly linked to employee turnover behavior, with a one-unit increase in the neuroticism score raising the probability of an employee becoming a former employee by 0.6%.

These findings have implications for firm managers looking to gain insights into employee online review behavior and improve firm performance. Online employee review websites are recommended to include the identified personality traits.

This study identifies employee personality traits from automated analysis of employee-generated data and verifies their relationship with employee satisfaction and employee turnover, providing new insights into the development of human resources in the era of big data.

Online employee reviews have a substantial impact on employee recruitment, retention and the overall perception of a company’s image, making them a crucial element of its online reputation. Consequently, these reviews play a vital role in shaping the company’s competitiveness in the talent market. This study aims to investigate the role of employee loyalty in online reputation in the tourism and hospitality sector.

This study collected online reviews posted by 334,428 employees across 173 companies in the tourism and hospitality sector. Then, this study proposed a method for measuring employee loyalty toward the company through text comments. Furthermore, the role of employee loyalty in online reputation through regression models was analyzed.

Employee loyalty is positively associated with the closed-form evaluations, and the length and readability of open-ended comments is directly and positively associated with review helpfulness and is indirectly associated with review helpfulness through employee online reviews. Employees’ perception of job instability has a significant moderating effect on the above relationships.

This study contributes to the literature on loyalty in the tourism and hospitality industry, online reputation and employee risk perception. These findings offer a more profound understanding of the extra-role behaviors demonstrated by loyal employees, provide a theoretical foundation for the formation of a company’s online reputation and contribute to helping the tourism and service industry better address risk events. These conclusions provide valuable insights for companies in the fields of human resource management and online reputation management.

To the best of the authors’ knowledge, this study is the first to reveal the impact of employee loyalty on the company’s online reputation and provides important theoretical and practical implications for management.

Employment exchanges have been playing a significant role in the worldwide labor market for more than a hundred years now. In India, since 1946, millions of aspiring Indian youths have registered themselves with the government-run employment exchanges to find a job. About four million job seekers got registered at 1,000 employment exchanges in India, it is important to analyze the placement statistics of these exchanges. In recent years, new methods of job search have evolved. This study examines whether employment exchanges are effective in the changed scenario?

Using state-level employment exchange data for the period 2010–2011 to 2019–2020, this study analyzes the determinants of job placement at employment exchanges in India. A critical analysis of the functioning of employment exchanges along with recommendations to improve the job search ecosystem in India is also presented in the study.

This study found that increased share of service sector in the state economy negatively impacts placement at employment exchanges.

The absence of focus on the service sector requires policy intervention if Indian employment exchanges are to remain relavant.

The government administration should rethink that ignoring service sector employment potential is unaffordable for an emerging economy and employment exchanges should be aligned accordingly.

About 30 million people are unemployed in India. If employment exchanges are transformed, it can have far-reaching socio-economic advantages.

This study is the first sub-country level study on the institution of employment exchanges. This study comprehensively maps the landscape of career services in India. Empirically establishing the impact of sectoral structure of economy on efficacy of employment exchanges, and makes the case for policy intervention that is needed to keep the employment exchanges relevant in India.

The purpose of this study is to analyze the nonlinear effects of corporate philanthropy on the responses of both internal and external stakeholders as well as its impact on corporate financial performance.

Based on the stakeholder theory, the authors developed a conceptual model to examine the nonlinear effects of corporate philanthropy on company performance. For the empirical analysis, data from 397 company-years was analyzed using a using a Heckman two-stage model. The robustness of the findings was also confirmed through panel regression analysis.

The study revealed a linear relationship between corporate reputation and corporate philanthropy, whereas job satisfaction exhibited a nonlinear relationship with corporate philanthropy.

This research bridges the gap in extant literature by scrutinizing the nonlinear associations between corporate philanthropy and financial performance. Additionally, it addresses an emerging scholarly demand to uncover the “dark side” of corporate philanthropy through an investigation into its adverse impacts on employee satisfaction. Moreover, the study augments existing understandings of stakeholder theory and corporate philanthropy, positing that the influence of corporate philanthropy, as conceptualized through stakeholder theory, hinges on perceived fairness in multilateral relationships.

Organizations widely adopt knowledge management (KM) to develop and promote technologies and improve business effectiveness. Analytics can aid in KM, further augmenting company performance and decision-making. There has been significant research in the domain of analytics in KM in the past decade. Therefore, this paper aims to examine the current body of literature on the adoption of analytics in KM by offering prominent themes and laying out a research path for future research endeavors in the field of KM analytics.

A comprehensive analysis was conducted on a collection of 123 articles sourced from the Scopus database. The research has used a Latent Dirichlet Allocation methodology for topic modeling and content analysis to discover prominent themes in the literature.

The KM analytics literature is categorized into three clusters of research – KM analytics for optimizing business processes, KM analytics in the industrial context and KM analytics and social media.

Systematizing the literature on KM and analytics has received very minimal attention. The KM analytics view has been examined using complementary topic modeling techniques, including machine-based algorithms, to enable a more reliable, systematic, thorough and objective mapping of this developing field of research.

The purpose of this study is to explore the perspectives of Generation Z college students regarding the job selection process, as well as the impact of digital technology on their career choices and job search endeavors.

Using the grounded theory methodology, the study used in-depth interviews with 15 participants to investigate the research inquiries.

The study identified six emerging themes related to the career aspirations of Generation Z students. The authors generated a job selection process model of Generation Z based on participants’ accounts of their recent job search experience. The model portrays the decision-making process performed by Generation Z job seekers while determining their career path.

To enhance comprehension of the job selection process among Generation Z individuals, future studies should incorporate a broader range of participants encompassing diverse cultural, social and economic backgrounds. Scholars have the potential to examine the relationships between Generation Z job seekers’ job selection, job performance and job satisfaction through a quantitative approach.

The six themes pertaining to optimal jobs for Generation Z can assist HR professionals in enhancing their understanding of the emerging pool of young and talented individuals. The utilization of the four-stage job selection process model may serve as a valuable tool for college career service professionals in the enhancement of tailored training programs.

This empirical study examines Generation Z job seekers’ attitudes toward their future profession, their perceptions of ideal occupations and the influence of technology on their search, preparation and selection processes for future careers.

Through a systematic literature review, this paper aims to endeavor to present a thorough historical perspective on the evolution of employee-based brand equity (EBBE), offering a comprehensive understanding of its development. The study explores the general model, causes and effects of EBBE, as well as the role of culture, leadership and brand management in building EBBE. The paper proposes an integrative framework to understand the interrelationships between the various dimensions of EBBE and offers practical guidelines for future research and the business world.

The paper uses a systematic literature review approach to analyze and synthesize 30 studies on EBBE retrieved from SCOPUS and Web of Science. The analysis involves a thematic and content-based examination of the literature, which is organized into three thematic groups.

The review highlights the importance of EBBE as a driver of organizational performance and success. The paper identifies the evolution of the major themes, trends and debates in the literature and suggests areas for future research. It underscores the need for more qualitative, multi-level and longitudinal research on EBBE, as well as the exploration of the links between EBBE and other forms of brand equity.

This paper is one of the first systematic literature reviews of EBBE, offering a comprehensive and integrated view of the existing literature since the beginning of this concept. The paper’s originality lies in its proposed integrative framework that captures the interrelationships between the various dimensions of EBBE and provides practical guidelines for future research and the business world.