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The overall purpose of this study is to inform practitioners about the levers for improving their employee portals.

The authors introduce a theoretical model that is based on the DeLone and McLean IS success model, which considers the specific requirements of employee portals. They tested the associations between their model's success dimensions by using more than 4,400 employees' responses, which were collected in 12 companies across different industries. They applied structural equation modeling to carry out the causal analysis. In addition, within a performance‐based analysis, they further investigated the success dimensions' improvement potentials.

The results of the causal analysis indicate that besides the factors contributing to the success of information systems (IS) in general, other success dimensions – like the quality of the collaboration and process support – have to be considered when aiming for a successful employee portal. The performance‐based analysis emphasizes the significance of collaboration quality to improve an employee portal and indentifies the respective fields of action.

This paper's contribution to theory is the empirical validation of a model for investigating employee portal success. The performance‐based analysis further elaborates on the causal analysi's findings. The results advance theoretical development in the area of employee portals and serve as a basis for future research in this field.

This model offers a means for organizations to evaluate and predict the success of employee portals. The study's findings make it possible for practitioners to understand the levers with which to improve their employee portals and to prioritize their investments accordingly.

This study is among the first, which empirically validates a comprehensive success model for employee portals and highlights its practical usefulness by means of a performance‐based analysis.

The purpose of this paper is to empirically assess the payoffs of a corporate portal in an academic institution in Oman and its impacts on business processes and employees.

The study included 100 employees, mostly instructors, in an academic institution. The questionnaire included indicators related to the portal usage, employees’ benefits (learning, adaptability and job satisfaction) and business processes’ benefits (effectiveness, efficiency and innovativeness) constructs. Data were analyzed by PLS‐Graph 3.0, a variance‐based structural equation modeling software.

Results revealed that corporate portal has significant returns on employees’ learning, adaptability and job satisfaction, and business processes’ effectiveness, efficiency and innovation. All six hypotheses in this study were supported.

The paper provides empirical evidence for practitioners and researchers on the benefits of a corporate portal in an academic institution in Oman.

Although much has been written about the challenges facing businesses in the 21st century, perhaps most daunting is the notion that if a company is to excel, it needs to continuously develop and nurture its knowledge‐based workforce. To do so, the company's fundamental work resources — information technologies, organizational policies and practices, and places of work — need to be fully synchronized to incent and support the knowledge work specific to the company's vision and goals. As technology and the forces of a global economy have changed the way business is done, so has the very nature of work changed. New work realities have created a new environment in which people and processes succeed only when barriers of time and distance are overcome. When a company's employees, customers, and facilities are widespread, establishing a reliable, cost effective support infrastructure that keeps people connected to needed resources and to colleagues and customers is essential. Real estate continues to play a key role in this new work environment, but an effective infrastructure design must integrate all of the key people, place and technology aspects. To do this, a true “systems”approach for providing work infrastructure is required.

Aims to review the key concepts of competency management (CM) and to propose method for developing competency method.

Examines the CM features of 22 CM systems and 18 learning management systems.

Finds that the areas of open standard (XML, web services, RDF), semantic technologies (ontologies and the semantic web) and portals with self‐service technologies are going to play a significant part in the evolution of CM systems.

Emphasizes the beneficial attributes of CM for private and public organizations.

Enterprise information portals and report‐based information management solutions can provide easy and cost‐effective presentation of information of any kind, especially ERP‐generated reports, to the desktops in an enterprise.

This paper attempts to discuss at a conceptual level on the concept of intranet effectiveness and further analyze the effectiveness model with several contributing factors grouped as organizational, technological and individual factors.

The paper's approach is a discussion of the issues.

First, the relationship between antecedent factors, i.e. organizational, technological and individual factors and intranet effective usage and intranet service quality as well as the consequences of these two factors on user performance warrants for more exploration. Second, through an understanding of antecedent factors with intranet effective usage and intranet service quality as well as the impact of these two factors on employee effectiveness, organizations may gain an understanding that could improve their intranet usage and service quality leading towards better employee performance. Lastly, since the effectiveness of intranet is directly or indirectly impact organizational effectiveness, a better understanding of intranet success would definitely promote towards clearer understanding of organizational success.

The proposed model adapts IS success model by Delone and Mclean and defines intranet effectiveness as a composite of intranet effective usage, intranet service quality and individual impact.

This study, based on the cognitive dissonance and commitment theories, aims to show that employees with high organizational commitment take more advantage of enterprise social networks (ESNs) due to work-related motivations. Furthermore, this study used the tricomponent attitude model to show that the employees' organizational concern and prosocial values mediate the impact of the organizational commitment on the work-related use of an ESN.

In all, 361 employees from seven Iranian companies using different ESN software packages were surveyed. The validity of the hypotheses was evaluated using partial least square–structural equation modeling (PLS-SEM).

The results of this study confirm that the employees' organizational commitment has a positive impact on their work-related use of the relevant ESN directly and through the mediating roles of their organizational concern and prosocial values.

Previous studies have carefully addressed the role of organizational commitment in the implementation of conventional information systems. However, this is among the few studies addressing the role of commitment in the work-related implementation of ESNs. The results of this study shed light on how employees with a high level of commitment toward the organizations for which they work take advantage of ESNs due to a work-related motivation for the accomplishment of their duties, for bringing benefits into the organization and for helping their coworkers.

The study adopts the conservation of resources (COR) theory for providing a better theoretical understanding of punitive supervision as an antecedent of employees’ minor deviant behaviors (namely, employee time theft and knowledge hiding) via creating cognitive mechanisms (employees’ perceived incivility). The purpose of this paper is to examine the moderating role of employees’ RESILIENCY on employees’ ability to buffer the impacts of punitive supervision.

Data was gathered from 265 frontline hospitality employees in Pakistan. A survey was administered in person to establish trust and rapport with employees and so, collect reliable data.

The findings confirmed a direct and mediated impact of punitive supervision on employee minor deviant behaviors via creating perceived incivility. The moderating role of employees’ resiliency was also confirmed, as the employees’ resiliency helped them mitigate the impact of punitive supervision on perceived incivility.

Data was collected from employees’ perceptions working in one industry and cultural setting. As employees’ perceptions (influenced by their cultural background) significantly affect their interpretations and reactions to punitive behavior, future research should validate and refine the findings by collecting data from a wider and diversified cultural and industry setting.

The findings provide theoretical explanatory power of the drivers and the contextual factors leading to minor employee deviant behaviors. The findings guide managers on how to develop pro-active and re-active strategies for deterring the occurrence and eliminating the consequences of punitive supervision.

This study contributes to the literature in multiple ways. It identifies and validates punitive supervision as an antecedent of Deviant Work Behavior (DWB). It provides a theoretical underpinning for explaining how punitive supervision spurs cognitive mechanisms, which in turn drive DWB. It also studies the nexus between destructive supervision and its outcomes in its entirety by studying the mediated and the moderating impacts of punitive supervision and perceived incivility, respectively.

Within the manufacturing sector, small- and medium-sized enterprises (SMEs) face specific challenges with regard to their strategic HRM capabilities. In this context, an emerging issue for both researchers and practitioners regards HR information systems (HRIS), i.e. the deployment of strategic IT capabilities to enable the firm’s high-performance work system (HPWS) capabilities and thus improve the performance of its HR function. The purpose of this paper is to address this issue by using a capability-based mediation perspective to study the strategic alignment of HR and IT.

A survey study of 206 manufacturing SMEs was realized and the data thus obtained was analyzed through structural equation modeling.

Results confirm that the HRIS capabilities of SMEs influence the performance of the HR function through their strategic alignment with the HPWS capabilities of these enterprises.

The results suggest that the manufacturing SMEs most active in developing their HRIS capabilities while developing their HPWS capabilities are most likely to develop a competitive advantage through the improved performance of their HR function. This is especially important in a time when firms of all sizes across the globe are waging a “war for talent,” and are enabled to do so by their strategic use of IT.

The results of the study constitute a valid basis for prediction and prescription with regards to the strategic alignment of human and IT resources.

To be more effective, artificial intelligence (AI) requires a broad overall view of the design and transformation of enterprise architecture and capabilities. Maturity models (MMs) are the recognized tools to identify strengths and weaknesses of certain domains of an organization. They consist of multiple, archetypal levels of maturity of a certain domain and can be used for organizational assessment and development. In the case of AI, quite a few numbers of MMs have been proposed. Generally, the links between AI technology, AI usage and organizational performance stay unclear. To address these gaps, this paper aims to introduce the complete details of the AI maturity model (AIMM) for AI-driven platform companies. The associated AI-Driven Platform Enterprise Maturity framework proposed here can help to achieve most of the AI-driven platform companies' objectives.

Qualitative research is performed in two stages. In the first stage, a review of the existing literature is performed to identify the types, barriers, drivers, challenges and opportunities of MMs in AI, Advanced Analytics and Big Data domains. In the second stage, a research framework is proposed to align company value chain with AI technologies and levels of the platform enterprise maturity.

The paper proposes a new five level AI-Driven Platform Enterprise Maturity framework by constructing a formal organizational value chain taxonomy model that explains a vast group of MM phenomena related with the AI-Driven Platform Enterprises. In addition, this study proposes a clear and precise description and structuring of the information in the multidimensional Platform, AI, Advanced Analytics and Big Data domains. The AI-Driven Platform Enterprise Maturity framework assists in identification, creation, assessment and disclosure research of AI-driven platform business organizations.

This research is focused on the basic dimensions of AI value chain. The full reference model of AI consists of much more concepts. In the last few years, AI has achieved a notable drive that, if connected appropriately, may deliver the best of expectations over many application sectors across the field. For this to occur shortly in machine learning, especially in deep neural networks, the entire community stands in front of the barrier of explainability. Paradigms underlying this problem fall within the so-called eXplainable AI (XAI) field, which is widely acknowledged as a crucial feature for the practical deployment of AI models in industry. Our prospects lead toward the concept of a methodology for the large-scale implementation of AI methods in platform organizations with fairness, model explainability and accountability at its core.

AI-driven platform enterprise maturity framework can be used for better communicate to clients the value of AI capabilities through the lens of changing human-machine interactions and in the context of legal, ethical and societal norms.

The authors discuss AI in the enterprise platform stack including talent platform, human capital management and recruiting.

The AI value chain and AI-Driven Platform Enterprise Maturity framework are original and represent an effective tools for assessing AI-driven platform enterprises.