Search results

The purpose of this paper is to answer two research questions: what are the ERP resources and organizational complementary resources (OCRs) required to achieve each group of benefits? And on the basis of its resources, when should an organization invest more in ERP resources and/or OCRs so that the potential value of its ERP is realised?

Studying 12 organizations in different countries and validating the results with 8 consultants.

ERP benefits realization capability framework is developed; it shows that each group of benefits requires ERP resources (classified into features, attached technologies and information technology department competences) and OCRs (classified into practices, attitudes, culture, skills and organizational characteristics) and that leaping ahead to gain innovation benefits before being mature enough in realising a firm’s planning and automation capabilities could be a waste of time and effort.

It is qualitative study. It needs to be backed by quantitative studies to test the results.

Although the “P” in ERP stands for planning, many academics and practitioners still believe that ERP applies to automation only. This research spotlights that the ability to invest in ERP can increase the innovation and planning capabilities of the organization only if it is extended and grown at the right time and if it is supported by OCRs. It is not cost effective to push an organization to achieve all the benefits at the same time; rather, it is clear that an organization would not be able to enjoy a higher level of benefits until it achieves a significant number of lower-level benefits. Thus, investing in higher-level benefit assets directly after an ERP implementation, when there are no organizational capabilities available to use these assets, could be inefficient. Moreover, it could be stressful to users when they see plenty of new ERP resources without the ability to use them. Although it could be of slight benefit to introduce, for example, business intelligence to employees in the “stabilizing period” (Badewi et al., 2013), from the financial perspective, it is a waste of money since the benefits would not be realised as expected. Therefore, orchestrating ERP assets with the development of organizational capabilities is important for achieving the greatest effectiveness and efficiency of the resources available to the organization. This research can be used as a benchmark for designing the various blueprints required to achieve different groups of benefits from ERP investments.

This research addresses two novel questions: RQ1: what are the ERP resources and OCRs required to achieve the different kinds of ERP benefits? RQ2: when, and on what basis, should an organization deploy more resources to leverage the ERP business value?

The purpose of this paper is to examine how managers orchestrate, bundle and leverage resources from big data for value creation in emerging economies.

The authors grounded the theoretical framework in two perspectives: the resource management and entrepreneurial orientation (EO). The study utilizes an inductive, multiple-case research design to understand the process of creating value from big data.

The findings suggest that EO is vital through which companies based in emerging economies can create value through big data by bundling and orchestrating resources thus improving performance.

This is one of the first studies to have integrated resource orchestration theory and EO in the context of big data and explicate the utility of such theoretical integration in understanding the value creation strategies through big data in the context of emerging economies.

The purpose of this study is to investigate the factors that influence the development of human capital by examining the interplay between different organizational mechanisms, including leadership, organizational culture and human resources management (HRM) practices. This study aims to enhance our understanding of how knowledge exchange influences human capital, with a specific focus on the unique context of Dubai, an area and context that have been underexplored in this research domain.

This study used a survey-based approach, involving 611 participants working across different sectors based in Dubai. This study used partial least squares structural equation modeling as the statistical analysis method.

The results of the study indicate that leadership behaviors have a predictive influence on organizational culture. In turn, organizational culture significantly affects knowledge exchange. Additionally, the study reveals that commitment-based HRM practices play a significant moderating role in the relationship between organizational culture and knowledge exchange.

This study contributes to the existing literature by providing valuable insights into the interplay between leadership, organizational culture and commitment-based HRM practices. By exploring these factors and their influence on knowledge exchange and human capital, the study enhances both the theoretical understanding and practical application in this field.

This study empirically investigates how the COVID-infodemic manifests differently in different languages and in different countries. This paper focuses on the topical and temporal features of misinformation related to COVID-19 in five countries.

COVID-related misinformation was retrieved from 4,487 fact-checked articles. A novel approach to conducting cross-lingual topic extraction was applied. The rectr algorithm, empowered by aligned word-embedding, was utilised. To examine how the COVID-infodemic interplays with the pandemic, a time series analysis was used to construct and compare their temporal development.

The cross-lingual topic model findings reveal the topical characteristics of each country. On an aggregated level, health misinformation represents only a small portion of the COVID-infodemic. The time series results indicate that, for most countries, the infodemic curve fluctuates with the epidemic curve. In this study, this form of infodemic is referred to as “point-source infodemic”. The second type of infodemic is continuous infodemic, which is seen in India and the United States (US). In those two countries, the infodemic is predominantly caused by political misinformation; its temporal distribution appears to be largely unrelated to the epidemic development.

Despite the growing attention given to misinformation research, existing scholarship is dominated by single-country or mono-lingual research. This study takes a cross-national and cross-lingual comparative approach to investigate the problem of online misinformation. This paper demonstrates how the technological barrier of cross-lingual topic analysis can be overcome with aligned word-embedding algorithms.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-09-2020-0417

The purpose of this paper is to analyse the research trends in the field of open and distance learning (ODL) as reflected in journal articles.

It compares research articles published in 2005 and 2015. Content analysis was conducted on a total of 288 research articles published in seven peer-reviewed journals on ODL. The study covers research areas and keywords, research methodology and participant types, and author collaboration.

The results show that macro-level research on areas such as globalization and cultural aspects of ODL remain relatively scarce, and international collaboration appear uncommon in both 2005 and 2015. However, there was an increasing amount of international collaboration in developing macro-level research. Empirical research studies, especially those using quantitative methods, have become the dominant methodology. The data sources have also been broadened. Several new keywords which did not exist or were rarely used (e.g. massive open online courses) have become common in 2015.

The analysis offers insights for researchers into how they can develop their research effectively in the field and enhance the chances of their research outputs being accepted. Recommendations are also made for ODL researchers on the types of research that tend to be accepted for publication and will have a high potential impact in the future.

This study empirically examines the effect of shop‐floor communication on implementation effectiveness of process management practices, and on the corresponding quality performance gained through process management implementation. It deals with four types of communication on the shop floor (small group problem solving, feedback, instructive communication, supervisory interaction facilitation) and three process management practices (process control, preventive maintenance, housekeeping).

Analysis of variance (ANOVA) and regression techniques were used to test the hypothesized relationships. Data were collected from 238 manufacturing plants through a questionnaire survey conducted in eight countries to develop reliable and valid measurement scales for operations management.

The statistical results demonstrate the positive effect of shop‐floor communication on the implementation of process management practices and the resultant quality performance. The results also suggest that each type of shop‐floor communication differently affects the way in which process management practices are implemented to influence quality performance.

Although the existing literature of quality management highlights the importance of communication and information management for the successful implementation of quality management, little detailed study has been conducted on how specific types of communication support quality management practices to obtain quality performance. This study contributes to the literature by breaking down communication into four types and providing specific empirical evidence on the relationship between each type of communication, process management practices, and quality performance.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

This paper identified that human capital is a key determinant in the success and performance of an organization. The paper also identified leadership as an important influence in terms of how human capital is managed.

The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

The practice of cronyism is a pervasive problem for most businesses and a great hindrance for employees, but empirical literature on its outcomes is scant. In light of such gaps, the objective of this study is to examine the relationship between organizational cronyism and employees' silence behavior through the mediating role of felt violation and the moderating role of continuance commitment.

A time-lagged cross-sectional survey comprising 226 respondents is carried out in a metropolitan city of a developing country (Lahore, Pakistan). The respondents were selected using the convenience sampling technique.

The findings reveal that organizational cronyism influences employees' silence (acquiescent and quiescent) both directly and indirectly (via felt violation). However, continuance commitment was noted to work as a boundary condition only between felt violation and quiescent silence.

Although the study deals with common method bias by collecting data in two waves, it may restrict causality. The findings not only have implications for the academicians, but also contribute to the conservation of resources theory. This study suggests organizations develop and implement a comprehensive intervention strategy that focuses on both prevention and damage control as a result of organizational cronyism.

Drawing upon the conservation of resources theory, this study adds value to the literature by empirically investigating the outcomes of cronyism at work. Moreover, the outcomes and mechanisms under consideration have largely been ignored in the literature.

The environment in high-tech industries is highly dynamic, and after COVID-19, it has become even more unpredictable. Hence, it has become critical for firms to develop strategies to cope with a highly dynamic environment. This paper aims to analyze how the impact of the scientific collaboration networks with URIs (universities and research institutes) on firm innovation performance is contingent on technological and market dynamics.

Using a sample of 174 Chinese firms in the new-energy vehicle industry during 2004–2015, the authors applied a random-effects negative binomial modeling approach to model these relationships.

A broad and strong scientific collaboration network promotes firm innovation network effects are contingent on technological and market dynamics. While technological dynamics strengthen the effect market dynamics weaken it due to the different purposes of collaboration for firms and URIs.

Firms should adjust the structure of scientific collaboration networks with URIs when facing different environments. The government should encourage firms to jointly research with diverse URIs and play an active role in stabilizing market environments.

This study contributes to the academic debate on university-industry scientific collaborations. Applying the temporary competitive advantage (TCA) framework, we provide nuances to the literature that studies the factors that condition the effects of networks. This study also adds to the research on firm scientific collaboration networks by measuring networks based on the coauthorship between firms and URIs.

The numerous spoil grounds brought about by mega transportation infrastructure projects which can be influenced by the ecological environment. To achieve better management of spoil grounds, this paper aims to assess their comprehensive risk levels and categorize them into different categories based on ecological environmental risks.

Based on analysis of the environmental characteristics of spoil grounds, this paper first comprehensively identified the ecological environmental risk factors and developed a risk assessment index system to quantitatively describe the comprehensive risk levels. Second, this paper proposed a comprehensive model to determine the risk assessment and categorization of spoil ground group in mega projects integrating improved projection pursuit clustering (PPC) method and K-means clustering algorithm. Finally, a case study of a spoil ground group (includes 50 spoil grounds) in a mega infrastructure project in western China is presented to demonstrate and validate the proposed method.

The results show that our proposed comprehensive model can efficiently assess and categorize the spoil grounds in the group based on their comprehensive ecological environmental risk. In addition, during the process of risk assessment and categorization of spoil grounds, it is necessary to distinguish between sensitive factors and nonsensitive factors. The differences between different categories of spoil grounds can be recognized based on nonsensitive factors, and high-risk spoil grounds which need to be focused more on can be identified according to sensitive factors.

This paper develops a comprehensive model of risk assessment and categorization of a group of spoil grounds based on their ecological environmental risks, which can provide a reference for the management of spoil grounds in mega projects.