Search results

The purpose of this study is twofold: to investigate the role of big data in firms’ co-knowledge and value creation and to understand the underlying drivers behind value creation through big data in the oil and gas industry by underscoring the role of firms’ capabilities, trends and challenges.

Following an inductive approach, semi-structured interviews were conducted with senior managers and analysts working in oil and gas companies across eight countries. The data collected from these key informants were then analysed using the qualitative data analysis software ATLAS.ti.

Value creation through big data is an important factor for enhancing performance. It has a positive impact on both tangible (organisational performance) and intangible (societal) aspects depending on the context. Oil and gas companies understand the importance of big data to creating value in their operations. However, implementing and using big data has been problematic. In this study, a framework was developed to show that factors such as the shortage of data experts, poor data quality, the risk of cyber-attacks and unsupportive organisational cultures impede its implementation and utilisation.

The findings from this study have implications for managers and executives implementing big data and creating value across various data-intensive industries. The research findings, are contextual, however, and should be applied cautiously.

This study contributes to the value creation literature in the big data context. The findings identify the key areas to be considered for the effective implementation and utilisation of big data in the oil and gas sector. This study addresses a broad but under-explored issue (i.e. knowledge creation from big data and its implementation) and strengthens the academic debate within this research stream.

The purpose of this study is to develop a conceptual framework on knowledge loss in a manufacturing sector based on three aspects: likelihood of knowledge loss, critical areas of knowledge loss and relevance of each of these knowledge areas in terms of utilization and alignment with organizational goals and strategy. Such a conceptual framework can be helpful to the practicing managers in understanding the types of knowledge that is lost of a given departing employee and thus deciding on a measure to retain the critical employees or capture their knowledge before they leave.

Using a case study approach, data has been collected from a multinational battery manufacturing company based in Hong Kong. Semi-structured interviews have been conducted and analyzed through CAQDAS ATLAS.ti to generate the themes which were then used to develop the conceptual framework.

The findings revealed that the likelihood factors of knowledge loss in the manufacturing sector include layoffs, retirement, immigration and job change. The critical areas of knowledge loss comprise the knowledge of relationships and networks, especially with the customers and suppliers, the technical knowledge (battery and process technology) and knowledge of management, among others. The relevance of each of these knowledge areas needs to be determined through proper analysis whether these knowledge areas are needed in future projects, up to date and aligned with organizational goals and strategy along with other factors.

Using the developed conceptual framework, managers and executives can identify critical employees in the manufacturing sector and accordingly take some appropriate measures to retain their knowledge. Caution should be taken while applying the findings of this study in other industries and context.

This paper is an attempt to reduce the dearth of empirical studies by exploring knowledge retention in the manufacturing sector, especially in the development of proper conceptual frameworks to assess the potential knowledge loss of employees.

As sustainable performance has a central role in the small and medium enterprises (SMEs) performance literature, this study aims to examine the influence of networking capabilities in enhancing sustainable performance through knowledge workers’ productivity and digital innovation. It also examines the sequential mediating role of knowledge workers’ productivity and digital innovation on networking capabilities and SMEs’ sustainable performance relationship.

Data were collected from 308 knowledge workers in the information technology sector and analyzed using the Hayes Process Macro bootstrapping method to test the proposed hypotheses.

Results indicate that knowledge workers’ productivity and digital innovation individually and sequentially mediate the relationship between networking capabilities and SME’s sustainable (economic and environmental) performance, surprisingly, they do not act as a mediator between networking capability and SME’s social performance. SMEs should prioritize investments in the professional development of their knowledge workers through training and skill enhancement programs. This investment equips knowledge workers with the tools to effectively use the knowledge and resources acquired through networking. Thus, knowledge workers may improve performance by using these resources to tackle challenges.

Although this research focused on this specific context, it is prudent to acknowledge that additional factors may also exert influence on sustainable performance within SMEs, factors that managers may consider when making decisions. Methodologically, the cross-sectional design of this research poses a potential limitation, as it does not allow for the complete elimination of endogeneity concerns. However, it is worth noting that scholars have endorsed the use of cross-sectional data in cases where management researchers aim to expand beyond well-documented and longitudinal data sets.

This research offers practical recommendations for SMEs to improve their sustainable performance through networking. SMEs should seek partnerships with complementary knowledge to improve operations and for other performance-oriented benefits.

This study adds significantly to the literature on sustainable SME performance by studying the interdependent effects of networking capabilities. It also represents the individual and sequential mediation mechanism that links networking capabilities to SME success through knowledge worker productivity and digital innovation.

Drawing upon the theoretical underpinning of knowledge worker productivity, this study aims to examine the relationship between abusive supervision and knowledge management (KM) process (creation, application and sharing of knowledge) and its impact on the knowledge worker productivity in knowledge-intensive organizations.

Hypothesis were tested through PROCESS Macro in IBM SPSS v.26 on a sample of 204 employees working in banking sector of Pakistan. Confirmatory factor analysis was conducted to test the model fitness through AMOS v. 26.

The results showed that the relationship between abusive supervision and KM process (creation, application and sharing of knowledge) is negative and highly significant, i.e. greater the abusive supervision in the banking sector, the lower is the engagement in KM processes. Furthermore, there is a positive and highly significant relationship between the KM process and knowledge worker productivity. Finally, the study indicates the negative impact of abusive supervision on the knowledge worker productivity through the mediating mechanism of knowledge management processes.

A key limitation is that the study is cross-sectional, and the findings may only be generalizable to developing countries context.

Previous studies have focused on supervisor–employee relationship but not in the context of knowledge worker productivity. This article fulfills this gap through understanding the impact of abusive supervision on the knowledge worker productivity in relation to KM processes (knowledge creation, sharing and application) by drawing upon the theoretical underpinning of knowledge worker productivity.

The purpose of this paper is to explore the relationship between big data and knowledge management (KM).

The study adopts a qualitative research methodology and a case study approach was followed by conducting nine semi-structured interviews with open-ended and probing questions.

Useful predictive knowledge can be generated through big data to help companies improve their KM capability and make effective decisions. Moreover, combination of tacit knowledge of relevant staff with explicit knowledge obtained from big data improvises the decision-making ability.

The focus of the study was on oil and gas sector, and, thus, the research results may lack generalizability.

This paper fulfills an identified need of exploring the relationship between big data and KM which has not been discussed much in the literature.

Retaining critical knowledge is relevant for all organizations, knowledge-intensive ones in particular. Failure to do so can, in the worst case, lead to an organization being unable to act. Acknowledging the role of context in this regard, the purpose of this paper is to examine knowledge retention (KR) in the banking sector of a developing country. A particular focus is placed on exploring various contextual factors that influence the retention of critical knowledge taking into consideration the setting.

Following a qualitative research design, semi-structured interviews were conducted with senior managers from private and public banks in Pakistan. Thematic analysis was used to analyze the data.

The findings suggest that the existence of a collectivist society, gender differences, few job opportunities, power distance and the late IT Boom are vital factors to be considered regarding KR in the setting studied. The findings are summarized in a conceptual framework that highlights critical factors of KR to be studied in a broader context and which are viewed as relevant for informing future research in this underdeveloped area of knowledge management (KM).

The data were collected from a small number of individuals working in different banks in only one country. Future studies should consider research designs across multiple organizations involving more people representing different roles, functions and age groups.

Existing KM research has emphasized the role of context while research on KR is underdeveloped in this regard. By exploring different contextual factors this study advances current understanding in the KM domain.

The purpose of this paper is to investigate the critical types of knowledge lost when employees depart companies in the oil and gas field.

The study adopts a grounded theory methodology. Twelve semi-structured interviews were conducted with elite informants in the oil and gas sector to gain an in-depth insight into the research problem. ATLAS.ti was used for data analysis and coding.

In the oil and gas industry, employees generally have job rotation and work at various geographical locations during their career. The departing employees possess valuable types of knowledge depending on the role and duties they have performed over the years. These include specialized technical knowledge, contextual knowledge of working at different geographical locations, knowledge of train wrecks and history of company, knowledge of relationships and networks, knowledge of business processes and knowledge of management.

The study findings might only be applicable to the oil and gas sector.

This paper fulfills an identified gap on the identification of critical areas of knowledge loss when employees depart from oil and gas companies. The study adds to the existing body of literature on this underexplored area in the knowledge management literature.

The purpose of this paper is to investigate how companies are handling the issue of knowledge retention from old age retiring workers in the oil and gas sector. This is achieved by providing a detailed insight on the challenges and strategies related to knowledge retention through study of companies from different geographical locations across the globe.

The study adopts a qualitative research methodology and 20 semi-structured interviews, with open-ended and probing questions, were conducted to gain an in-depth insight into the knowledge retention phenomena.

Knowledge retention activities tend to be inconsistent in majority of the oil and gas companies, with not much work being done regarding knowledge loss from old employees, partly because of the fall in oil prices and layoffs. Oil prices turn out to be a decisive factor in oil and gas industry regarding workforce and knowledge retention activities. The political situation and geographical locations of the companies also affect the knowledge retention activities. Moreover, the aging workforce and retirement issue is more acute in the upstream sector.

The focus of the study was on the oil and gas sector, and thus the research results may lack generalizability.

This paper fulfills an identified need for investigating the issues and challenges of knowledge retention regarding old age retiring employees by taking into account a global perspective and providing a comparison among different companies in different geographical locations.

Recent research has highlighted the beneficial role of supply chain resilience for ensuring efficient production and business processes. The purpose of this study is to explore enablers of supply chain resilience. In particular, the authors examine whether and how dynamic capabilities and knowledge management can help firms develop a resilient supply chain in times of high disruption and uncertainty.

A single longitudinal case study design was adopted. Data was collected over 8 years from a Pakistani textile producer and supplier through semi-structured interviews and was analyzed through NVivo to generate codes and themes that contributed to the development of the supply chain resilience model.

The analysis of case study shows that our focal firm strategically acquired, transferred and integrated market knowledge by investing in digital technologies and idiosyncratic resources and consequently developed a supply chain model that was resilient in addressing logistics and delivery challenges in uncertain & critical times.

The study brings together three main research streams of organizational theory, namely supply chain, knowledge management and dynamic capabilities, and proposes a nuanced resilient supply chain model.

By applying the research findings, managers can adjust, develop and adopt supply chain resilience to address market volatilities, thereby creating value and longevity in their supply chain operations. However, the findings are context specific and should be applied cautiously.

The outcomes provide early hints on how companies in emerging economies can adopt and integrate novel digital technologies, and overhaul their organizational routines to facilitate knowledge management and develop dynamic capabilities, and consequently enhance the resilience of their supply chain operations.

Drawing on the entrepreneurial event model (EEM), entrepreneurship education programs (EEPs) and perceived contextual support (adapted from social cognitive career theory) and perceived contextual barriers, this study aims to unravel the differences in entrepreneurial activity among university students in higher education institutes in two diverse Asian countries.

This study uses a cross-sectional survey-based data collection technique using paper and electronic methods. The study analyzes data using descriptive statistics, principal component analysis, reliability analysis and logistic regression analysis via SPSS version 25.

The findings show the positive influence of perceived desirability and feasibility on entrepreneurial intentions; however, the stronger desirability was found among university students in China and stronger feasibility toward entrepreneurial intentions among Pakistani students. The study reveals the negative significant influence of EEPs on entrepreneurial intentions, and this finding is consistent across both samples. Furthermore, the findings show that university students in both countries show insignificant impact of perceived contextual support in predicting entrepreneurial intentions. Finally, the study confirms the negative influence of perceived barriers on entrepreneurial intentions in both contexts.

This study provides differences in entrepreneurial activity by combing EEM, EEPs, perceived contextual support and barriers in two diverse Asian countries, and to the best of author’s knowledge, no previous study considered these factors in a single framework. Furthermore, the findings of the study enrich existing literature and also provide policy recommendations for practitioners.