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Managers may underprice initial public offerings (IPOs), leading to higher initial returns (IRs). The purpose of this paper is multi-fold: to compensate investors for risk, to reduce litigation risk, as well as to maintain control over the firm. The authors examine country-level contingencies (degree of investor protection, legal origin and degree of transparency) in OECD countries to explain IPO IRs.

Cross-sectional data comprising of 4,164 IPOs from 28 OECD countries are used for the period of 2005-2010. Ordinary least square using multiple linear regressions is used to test the hypotheses.

Investors’ protection is associated with higher IRs. This relationship is stronger in the non-common law countries. Degree of transparency negatively moderates the relationship in common law countries. Overall, the results show evidence of risk compensation, litigation risk reduction, and managerial control motives in underpricing.

IPO IRs in OECD countries is examined, within the boundaries of institutional characteristics, i.e., investors’ protection, legal origin and transparency level.

The empirical support for agency theory explanations for the great variance in CEO pay has been equivocal. Drawing from the performance appraisal literature, we hypothesize that boards of directors incorporate human judgment into the evaluation and reward of CEO performance in order to balance managerial risk with agency costs. We test Baysinger and Hoskisson’s (1990) proposition that insider‐dominated corporate boards rely on subjective performance evaluation to reward the CEO, and we argue that R&D intensity influences this relationship. Using a sample of Fortune firms, findings support our contention that human judgment is important in evaluating and rewarding CEO performance.

The purpose of this paper is to show the applicability of data envelopment analysis (DEA) in arriving at an unbiased account of relative performance in a set of companies, using the pharmaceutical industry as an example.

A DEA‐based income efficiency measure of business performance for the pharmaceutical industry is computed. The pharmaceutical industry, which includes many multinational corporations with complex governance problems, and the strategies that allowed firm efficiency rankings to change over time, over ten recent years, are analyzed.

The analyses indicate that the inclines and declines in DEA efficiency rankings are related to the strategic choices made by the upper management.

The paper attempted to trace firm behavior post hoc to validate the DEA rankings. All relevant firm behavior may not have been captured; the paper only attempted to capture behavior reported in the respectable business press, which may introduce a bias.

The approach may be ideal to evaluate strategic managers (CEOs, general managers, and presidents) by board of directors, since it relates multiple performance indices to a meta‐measure of performance. Another group of beneficiaries include sector financial analysts. The approach adds a new dimension to sector analysis, to compare specific industries and identify the relative rankings of firms on multiple performance indices.

The paper demonstrates the usefulness of DEA in performance governance measurement by applying it to the pharmaceuticals industry.

Since corporate ventures operate under the organizational conditions of a parent company, this article aims to highlight key conditions influencing the success of a new venture.

Two cases of corporate venturing are analyzed regarding their performance since they are characterized by different conditions within one international consumer‐goods company. Hence, the literature on corporate entrepreneurship is reviewed and combined with a case study to explore the role and drivers of organizational conditions in the inception and development of new corporate ventures.

The case study reveals two key organizational differences pertaining to corporate new ventures — procedural clarity and procedural discipline. These differences mitigate the variety of risks that corporate entrepreneurs face and smooth or hinder their way to evolve their venture from ideas to business.

As the study includes two venturing cases within the same company in the fast moving consumer goods industry (FMCG), the findings are so far limited to the characteristics of this company type and its sector.

This article supports mid‐level managers to run corporate ventures more successfully by introducing a clear action plan with well defined phases. Individual managers' impact should be limited and linked to a more objective network‐structure.

In contrast to previous literature, this paper highlights the influence of organizational conditions under which corporate ventures are initiated and operated. Additionally, there are further factors identified, the ventures' internal visibility, and the knowledge support by the parent company, which will influence the venture's success or failure.

Intervention of artificial intelligence (AI) has brought up the issue of future job prospects in terms of the employability of the professionals and their readiness to harness the benefits of the AI. The purpose of this study is to recognize the implications of AI on employability by analyzing the issues in the health-care sector that if not addressed, can dampen the possibilities offered by AI intervention and its pervasiveness (Cornell University, INSEAD, and WIPO, 2019).

To get an insight on these concerns, an approach of total interpretive structural modelling, cross impact matrix multiplication applied to classification and path analysis have been used to understand the role of the critical factors influencing employability in the health-care sector.

This study primarily explores the driving-dependence power of the critical factors of the employability and displays hierarchical relationships. It also discusses measures which, if adopted, can enhance employability in the health-care sector with the intervention of AI.

Employability also has an impact on the productivity of the health-care service delivery which may provide a holistic opportunity to the management in health-care organizations to forecast the allocation and training of human resources and technological resources.

The paper attempts to analyze AI intervention and other driving factors (operational changes, customized training intervention, openness to learning, attitude toward technology, job-related skills and AI knowledge) to analyze their impact on employability with the changing needs. It establishes the hierarchical relationship among the critical factors influencing employability in the health-care sector because of the intervention of AI.

Spiritual tourism is becoming a significant growth area of the Indian travel market, with more Indians opting to go on pilgrimage to popular religious cities. There are many spiritual destinations where some of this life's essences can be sought to enjoy harmony and peace. The study aims to prioritize motivators driving the intentions of the tourists to visit the spiritual destination.

The current study applied the analytical hierarchical process, a multi-criteria decision-making technique, on the sample of visitors from all the six spiritual destinations to rank the motivational factors that drive the intentions of the tourist to visit a spiritual destination.

The study's results postulated that spiritual fulfillment motives and destination atmosphere are the top prioritized motivations, while destination attributes and secular motives emerged as the least prioritized.

The research study provides valuable insights to the spiritual tourism industry stakeholders to target the tourists' highly prioritized motivations to augment the visits to a particular spiritual destination.

Previous research has explored the motivations and modeled their relationships with tourists' satisfaction and intentions. But, the present study has applied a multi-criteria decision-making technique to add value to the existing knowledge base.

Massive open online courses (MOOCs) are among the most recent e-learning initiatives to gain widespread acceptance among universities. However, despite MOOCs' “much-documented” benefits, many questions are being raised late regarding the long-term sustainability of the open online teaching e-learning model. With high dropout rates in MOOCs courses, recent research has focused on the challenges limiting MOOCs’ growth. But most of the research is directed toward students’ perspectives, leaving the instructors’ perspective. One of the most important aspects of instructors’ perspective is the motivation for MOOCs' development and delivery.

The present study collected the data from 25 MOOC developers of Indian origin. To prioritize or rank the motivational factor behind developing a MOOC, a fuzzy-analytical hierarchical process (F-AHP) technique was applied to the data set. The primary motivational factors considered for the study were professional development, altruism, personal development, institutional development, intrigue, monetary benefits and peer influence.

The results showed that professional development and personal development are two prime motives that drive MOOCs development. Monetary benefits and peer influence were the least important factors among all the factors considered for the study.

Previous studies have identified and modeled the motivational factors that contribute toward developing MOOCs. However, there was little knowledge about the hierarchy among the motivating factors. The present study fills this gap by establishing the ranking of motivational factors responsible for MOOCs development.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-04-2021-0205.

In the era of digitalization and technology, tremendous changes have taken place in the taxi industry worldwide. The traditional taxi service has transformed into the latest innovative technology-based e-hailing service. There are innumerable factors that drive the user adoption of e-hailing apps. This study aims to primarily concentrate on identifying, analyzing and ranking these factors which have an impact on the user intention toward using e-hailing apps.

The e-hailing app users in the state of Punjab and Chandigarh are the target population for the study. A fuzzy analytical hierarchy process technique has been applied to analyze and codify the determinants that influence the user intention of adopting e-hailing apps. The primary factors that have been considered for the study are social influence, perceived usefulness, facilitating conditions, perceived ease of use, self-efficacy, perceived risk, compatibility and trust.

The study revealed that “Perceived Usefulness” is the factor that influences user intention to use e-hailing apps the most, while “Perceived Risk” the least. The sub-criteria codified in the top priority was as follows: “Overall, I find the e-hailing app useful in booking a taxi (C15)”; “I do not need some people to use e-hailing apps (C52); “I believe e-hailing app is compatible with existing technology (C61).” The sub-criterion “E-hailing app service provider keeps its promise (C72)” was demonstrated to have the least impact on the user intention of adopting e-hailing apps.

The study has been confined to only eight factors selected from the extended technological acceptance model framework and some related technology acceptance theories. Some more other factors may have an impact on user adoption of e-hailing apps, which need to be added further. Also, the scope of the study should be enhanced by expanding the geographical area beyond the selected region.

The findings of the study enable the e-hailing service providers and marketers to understand the users’ intention in a better way, to make improvements in e-hailing apps and formulate strategies accordingly.

The previous literature provides the base to the present study for identifying the factors affecting user behavioral intention toward e-hailing apps and information technology. The findings and results of the present research make value addition to the existing knowledge base.

The application of knowledge management (KM) is critical to public sector firm as it is to private sector firm. However, despite its significance, the academic enquiry of KM in public sector is at its nascent stage. This forms the motivation of the present work; this paper aims to analyze and understand the intricate relationship between KM processes and public sector firm performance in terms of operational, quality and innovation performance.

A comprehensive KM processes–performance framework consisting of seven constructs (four constructs of KM processes and three constructs of KM performance) and their underlying factors was developed through an extensive literature review. The employee perceptions of these seven constructs were captured on a five-point Likert scale using a country-wide survey in the UAE public sector. The 270 valid responses captured were then used to first validate the KM framework and then test the hypothesized relationships between KM processes and KM performance.

The findings show that all four KM processes (knowledge creation, knowledge capture and storage, knowledge sharing and knowledge application and use) had a positive and significant impact on operational, quality and innovation performance of public sector in the UAE.

The findings confirm the validity and reliability of all the seven constructs and their underlying factors and the assessment framework. Overall, this study fills a gap in the literature about applying/implementing a KM framework for the public sector and therefore significantly contributes toward the theoretical advancement of the field. However, the study does acknowledge the use of perceptual measures of individual employees as a limitation instead of more objective measures to capture the impact KM processes on KM performance.

The strong and significant impact of KM processes on firm performance is expected to provide the impetus for practitioners and policymakers to implement and leverage from KM processes and improve firm performance in the public sector.

A comprehensive development, validation and assessment of a KM framework for the public sector has not been attempted previously anywhere, let alone UAE, and hence constitutes the novelty of this work.