Wafa Khalaf Al Adwan and Marah Essam Al Safadi
This study aims to investigate the Jordanian Telecommunications Company's implementation of business analytics and how it affects the caliber of its financial reporting. The staff…
Abstract
This study aims to investigate the Jordanian Telecommunications Company's implementation of business analytics and how it affects the caliber of its financial reporting. The staff members of Jordanian telecom businesses will receive a questionnaire. Previous research has indicated that organizational, technological, and environmental factors have a significant role in influencing the choice to use business analytics. It is also anticipated that pressure from competitors, top management backing, and cost savings would all have a significant impact on the intention to use business analytics. These financial reports have improved in quality as a result. These anticipated outcomes demonstrate how crucial it is for businesses to employ business analytics as a tool to improve their financial performance and ability to compete in the global marketplace.
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Tayfun Yıldız, Betül Balkan Akan, Ünsal Sığrı and Marina Dabić
Tacit and explicit knowledge sharing play crucial roles in today’s rapidly changing business environment, particularly in fostering innovation. However, uncovering tacit knowledge…
Abstract
Purpose
Tacit and explicit knowledge sharing play crucial roles in today’s rapidly changing business environment, particularly in fostering innovation. However, uncovering tacit knowledge sharing remains complex. The purpose of this study is to analyze the mediating roles of tacit and explicit knowledge in the relationship between a knowledge-sharing culture and organizational creativity.
Design/methodology/approach
In this study, the authors developed an extended analytical process to analyze the impact of explicit and tacit knowledge on a knowledge-sharing culture and organizational creativity. This process combines two analytical techniques: necessary condition analysis (NCA) and partial least squares structural equation modeling (PLS-SEM). NCA identifies essential bottlenecks for a specific outcome, while PLS-SEM uncovers strong connections between predictor and outcome variables. The authors applied these analyses to a sample of 155 IT experts from a leading telecom company in the Turkish ICT industry to test the relevant hypotheses.
Findings
The findings of this study indicate that tacit knowledge, rather than explicit knowledge, partially mediates the relationship between a knowledge-sharing culture and organizational creativity. This mediating role of tacit knowledge is particularly pronounced in the ICT sector. Additionally, the impact of organizational capabilities on organizational creativity is amplified by higher levels of tacit knowledge sharing.
Originality/value
The effect of organizational capabilities on organizational creativity was found to increase because of tacit knowledge sharing compared to explicit knowledge sharing, depending on the knowledge-sharing climate.
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Anett Erdmann and Luis Toro-Dupouy
In higher education, the appreciation and implementation of artificial intelligence (AI) has led to debate and polarization. This study examines how the institutional environment…
Abstract
Purpose
In higher education, the appreciation and implementation of artificial intelligence (AI) has led to debate and polarization. This study examines how the institutional environment at universities impacts the value perception and intention to adopt AI in higher education. It seeks to optimize the adoption pathway by identifying essential “must-have factors” and “value drivers.”
Design/methodology/approach
Employing the technology-organization-environment (TOE) framework alongside the technology acceptance model (TAM) framework and perceived value concepts, this research utilizes a partial least squares structural equation modeling (PLS-SEM) approach complemented by necessary condition analysis (NCA), a novel approach in this context, which allows us to distinguish between critical antecedents and value drivers in the evaluation and adoption of AI technology.
Findings
Results indicate that organizational complexity, readiness, competency, compatibility and competitive advantage significantly affect the perceived value of AI, mediated by stakeholders’ perceptions of its ease of use and usefulness. These factors enhance the intention to adopt AI in higher education. Perceived usefulness has the highest effect size and the importance of ease of use differs between Europe and South America. External factors like partner support and competitive advantage are necessary considerations to be met, while competitive advantage and some internal factors are sufficient conditions for AI adoption.
Originality/value
The study underscores the importance of certain institutional factors, setting priorities for management actions in AI adoption. It differentiates between the general appreciation of AI and the intention of practical implementation, highlighting the role of partner support as a necessary condition, although a non-value-driving factor.
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Dewen Liu, Ying Zou, Peng Lv and Shanji Yao
While the impact of digitalization on businesses has been extensively studied, the influence of digitalization on marketing outcomes in private enterprises has not received…
Abstract
Purpose
While the impact of digitalization on businesses has been extensively studied, the influence of digitalization on marketing outcomes in private enterprises has not received sufficient attention. The current study aims to examine how and when digitalization affects international marketing decisions in the context of private enterprises.
Design/methodology/approach
This study employs data from a survey of Chinese private enterprises conducted in 2020, which constitutes the world's largest dataset of its kind. Nearly 19,000 samples were included in the study. Additionally, we also incorporate supplementary data on digitalization in the Chinese region. Employing various methods, this study empirically and robustly examines the proposed research framework within the context of Chinese private enterprises.
Findings
Based on the resource-based view and agency theory, this paper found that digitalization can positively impact private enterprises’ direct and indirect international marketing decisions. Furthermore, we introduce the inclusion of innovation capacity and board governance as moderators in the model and find that board governance attenuates the influence of digitalization on international marketing decisions, while innovation capacity enhances the impact of digitalization on direct international marketing but diminishes its effect on indirect international marketing.
Originality/value
This study advances the understanding of the impact of digitalization on international marketing in private enterprises, thereby addressing the gap in the limited focus on digitalization in private enterprises. It also demonstrates how private enterprises effectively utilize digitalization to gain marketing advantages in the international market.
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Peter Cronemyr, Anders Fundin and Lars Wemme
Process management principles are challenging owing to the increasing need for sustainable operations. The demand for rapid deliveries implies accelerated changes and increased…
Abstract
Purpose
Process management principles are challenging owing to the increasing need for sustainable operations. The demand for rapid deliveries implies accelerated changes and increased flexibility. Therefore, this study aims to facilitate process improvements based on change-driven needs.
Design/methodology/approach
The research is conducted using holistic multiple case studies of eight Swedish organisations (with employees from Sweden, France and Germany), representing the automotive, energy, medical technology, healthcare, telecom and social services sectors.
Findings
A process management model with four change-driven phases is presented. The model fulfils demands for both speed and quality in process changes, providing specific guidance on working methods for (1) control and stability, (2) creativity and stability, (3) creativity and change and (4) control and change.
Research limitations/implications
This research is limited to eight organisations in Sweden, France, and Germany that participate in the automotive, energy, medical technology, healthcare, telecom and social services sectors. Future research should explore broader international contexts.
Practical implications
The proposed model helps decision-makers adapt process management to evolving business and operational needs; thus, leaders can make grounded decisions on when and how to change operations based on changing internal and external requirements.
Originality/value
This study challenges the current process management paradigm with new knowledge of how process management can be adapted to new business opportunities.
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The study aims to provide a comprehensive understanding of the existing literature on women’s leadership in academia by identifying the existing challenges for their…
Abstract
Purpose
The study aims to provide a comprehensive understanding of the existing literature on women’s leadership in academia by identifying the existing challenges for their underrepresentation, and proposing a new-age leadership interventions to address the inherent systemic biases and develop foster an equitable academic climate.
Design/methodology/approach
The study employed bibliometric analysis to map the literature by investigating publication and geographical trends. Techniques like citation, co-citation, bibliographic coupling and co-word analysis identified seminal research and emerging themes, providing insights into research developments and facilitating identification of avenues for future research.
Findings
Our study highlights how social, organizational and individual barriers disadvantage women academic leaders. Existing enablers for women in leadership, like mentorship, leadership development and family friendly policies, focus on bringing change within the prevailing academic culture, reinforcing the notion “women need support”, overlooking the influence of systemic barriers. Such interventions are often ineffective in bringing sustainable change. We propose integrating AI/machine learning (ML) technologies in leadership selection to reduce bias arising from subjectivity.
Research limitations/implications
This study contributes to the discourse on gender inequality in academic leadership by offering a robust understanding of the research topic and informing avenues for future research.
Practical implications
Policymakers and higher education institutions can use the findings of the study to aid the formulation of policies, initiatives and institutional procedures to mitigate the prevalent gender bias in academia and cultivate an inclusive culture for growth of women.
Originality/value
The paper analyses women’s under-representation as academic leaders and proposes a novel data-driven intervention using gamification, AI and ML, aiming to reshape gender dynamics in academic leadership.
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Yanina Espegren and Mårten Hugosson
Human resource analytics (HRA) is an HR activity that companies and academics increasingly pay attention to. Existing literature conceptualises HRA mostly from an objectivist…
Abstract
Purpose
Human resource analytics (HRA) is an HR activity that companies and academics increasingly pay attention to. Existing literature conceptualises HRA mostly from an objectivist perspective, which limits understanding of actual HRA activities in the complex organisational environment. This paper therefore draws on the practice-based approach, using a novel framework to conceptualise HRA-as-practice.
Design/methodology/approach
The authors conducted a systematic literature review of 100 academic and practitioner-oriented publications to analyse existing HRA literature in relation to practice theory, using the “HRA-as-practice” frame.
Findings
The authors identify the main practices involved in HRA, by whom and how these practices are enacted, and reveal three topics in nomological network of HRA-as-practice: HRA technology, HRA outcomes and HRA hindrances and facilitators, which the authors suggest might actualize enactment of HRA practices.
Practical implications
The authors offer HR function and HR professionals a basic ground to evaluate HRA as a highly contextual activity that can potentially generate business value and increase HR impact when seen as a complex interaction between HRA practices, HRA practitioners and HRA praxis. The findings also help HR practitioners understand multiple factors that influence the practice of HRA.
Originality/value
This systematic review differs from the previous reviews in two ways. First, it analyses both academic and practitioner-oriented publications. Second, it provides a novel theoretical contribution by conceptualising HRA-as-practice and comprehensively compiling scattered topics and themes related to HRA.
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Marjut Hirvonen, Katri Kauppi and Juuso Liesiö
Although it is commonly agreed that prescriptive analytics can benefit organizations by enabling better decision-making, the deployment of prescriptive analytics tools can be…
Abstract
Purpose
Although it is commonly agreed that prescriptive analytics can benefit organizations by enabling better decision-making, the deployment of prescriptive analytics tools can be challenging. Previous studies have primarily focused on methodological issues rather than the organizational deployment of analytics. However, successful deployment is key to achieving the intended benefits of prescriptive analytics tools. Therefore, this study aims to identify the enablers of successful deployment of prescriptive analytics.
Design/methodology/approach
The authors examine the enablers for the successful deployment of prescriptive analytics through five organizational case studies. To provide a comprehensive view of the deployment process, each case includes interviews with users, managers and top management.
Findings
The findings suggest the key enablers for successful analytics deployment are strong leadership and management support, sufficient resources, user participation in development and a common dialogue between users, managers and top management. However, contrary to the existing literature, the authors found little evidence of external pressures to develop and deploy analytics. Importantly, the success of deployment in each case was related to the similarity with which different actors within the organization viewed the deployment process. Furthermore, end users tended to highlight user participation, skills and training, whereas managers and top management placed greater emphasis on the importance of organizational changes.
Originality/value
The results will help practitioners ensure that key enablers are in place to increase the likelihood of the successful deployment of prescriptive analytics.
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Mahesh Babu Purushothaman, Funmilayo Ebun Rotimi, Samadhi Samarasekara and Ali GhaffarianHoseini
This paper aims to highlight the factors affecting health and safety (H&S) and the SMART Technologies (ST) used to mitigate them in the construction industry through a range of…
Abstract
Purpose
This paper aims to highlight the factors affecting health and safety (H&S) and the SMART Technologies (ST) used to mitigate them in the construction industry through a range of selected papers to encourage readers and potential audiences to consider the need for intelligent technologies to minimize the risks of injuries, illnesses and severe harm in the construction industry.
Design/methodology/approach
This paper adopts a double systematic literature review (SLR) to analyse studies investigating the factors affecting H&S and the ST in the construction industry using databases such as Google Scholar, Scopus, Science Direct and Emerald Insight publication.
Findings
The SLR identified “fatal or focus five factors” that include objects Fall from heights (FFH) and trapped between objects; Falls, Trips and slips (FTS); Machinery/Equipment Malfunction and Moving Equipment; Pollutants: Chemicals, Airborne Dust, Asbestos; and Electrocution. The ST includes Safety Boots/SMART Glasses/SMART Helmet/SMART Vests/SMART PPE/SMART Watch, Mobile Apps, Building Information Modelling (BIM), Virtual Reality/Augmented Reality (VR/AR), Drones/Unmanned Aerial Vehicles and Wearable Technology/Mobile Sensors help mitigate the risk posed by “Fatal five”. However, other factors within the scope of ST, such as Weather Conditions, Vibrations, Violence, Disease and illness, Fire and Explosion and Over Exertion, are yet to be adopted in the field.
Research limitations/implications
SLR methodology limitations of not obtaining the most updated field knowledge are critical and are offset by choosing 72% of H&S and 92% of SM review literature post-2017. Limitations to capturing articles because of the restriction of database access: only English language search and journals that are not a part of the databases selected are acknowledged. However, key database search that recognizes rigorous peer-reviewed articles offset these limitations. The researcher’s Bias is acknowledged.
Practical implications
This paper unravels the construction H&S factors and their interlinks with ST, which would aid industry understanding and focus on mitigating associated risks. The paper highlights the Fatal five and trivial 15, which would help better understand the causes of the H&S risks. Further, the paper discusses ST’s connectivity, which would aid the organization’s overall H&S management. The practical and theoretical implications include a better understanding of all factors that affect H&S and ST available to help mitigate concerns. The operating managers could use the ST to reduce H&S risks at every construction process stage. This paper on H&S and ST and relationships can theorize that the construction industry is more likely to identify clear root causes of H&S and ST usage than previously. The theoretical implications include enhanced understanding for academics on H&S factors, ST and gaps in ST concerning H&S, which can be expanded to provide new insights into existing knowledge.
Originality/value
This paper highlights all factors affecting H&S and ST that help mitigate associated risks and identifies the “Fatal five” factors. The paper is the first to highlight the factors affecting H&S combined with ST in use and their interactions. The paper also identified factors within the ST scope that are yet to be explored.
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Hemlata Gangwar, Mohammad Shameem, Sandeep Patel, Alex Koohang and Anuj Sharma
Generative artificial intelligence (GenAI) can potentially improve supply chain management (SCM) processes across levels and verticals. However, despite its promise, the…
Abstract
Purpose
Generative artificial intelligence (GenAI) can potentially improve supply chain management (SCM) processes across levels and verticals. However, despite its promise, the implementation of GenAI for SCM remains challenging, mainly due to the lack of knowledge regarding its key drivers. To address this gap, this study examines the factors driving GenAI implementation in an SCM environment and how these factors optimize SCM performance.
Design/methodology/approach
A thorough literature review was followed to identify the drivers. The resultant model from the drivers was validated using a quantitative study based on partial least squares structural equation modeling (PLS-SEM) that used responses from 315 expert respondents from the field of SCM.
Findings
The results confirmed the positive effect of performance expectancy, output quality and reliability, organizational innovativeness and management commitment to GenAI usage. Further, they showed that successful GenAI usage improved SCM performance through improved transparency, better decision-making, innovative design, robust development and responsiveness.
Practical implications
This study reports the potential drivers for the contemporary development of GenAI in SCM and highlights an action plan for GenAI’s optimal performance. The findings suggest that by increasing the rate of GenAI implementation, organizations can continuously improve their strategies and practices for better SCM performance.
Originality/value
This study establishes the first step toward empirically testing and validating a theoretical model for GenAI implementation and its effect on SCM performance.